Intelligent Reasoning

Promoting, advancing and defending Intelligent Design via data, logic and Intelligent Reasoning and exposing the alleged theory of evolution as the nonsense it is. I also educate evotards about ID and the alleged theory of evolution one tard at a time and sometimes in groups

Thursday, January 05, 2017

Joe Felsenstein and Patrick May- Very stupid or willfully ignorant

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Here we go again, this time evos want to remain willfully ignorant of the fact that functional sequence complexity and complex specified information (biology) are the same exact things. They get confused because the metrics for each are different. It's as if they think that two different phrases cannot be talking about the same thing and that because there are two slightly different metrics then they must be different things.

Dembski/ Meyer CSI (biology) is supposed to be a mathematical measure of functional information of the functional sequence complexity observed in protein family biosequences as well as their RNA and DNA antecedents
Durston et al posit their own mathematical measure of functional information, in units of Fits, of the functional sequence complexity observed in protein family biosequences has been designed and evaluated.
They are both measuring the same thing. If you have CSI (biology) it is because you have functional sequence complexity. And if you are measuring the FSC then you are measuring the CSI.
Neither Joe Felsenstein nor Patrick May can grasp that simple explanation. The stupid runs deep...

posted by Joe G @ 11:37 AM  

62 Comments:

  • At 5:59 PM, Blogger Jerad said…

    . . .evos want to remain willfully ignorant of the fact that functional sequence complexity and complex specified information (biology) are the same exact things.

    Why are there two different terms then?

    They get confused because the metrics for each are different. It's as if they think that two different phrases cannot be talking about the same thing and that because there are two slightly different metrics then they must be different things.

    It is a fair point though. Perhaps it would be good to show they are the 'same thing'. How about an example?



    How about a worked out example: take some genetic sequence, like the fern genome perhaps, give the results of the two different metrics and then show that the two results are compatible based on the demonstration that what they are measuring is the same thing.

    It's a fair question and should be easy enough to do if what you say is true.

     

  • At 8:03 PM, Blogger Joe G said…

    Why are there two different terms then?

    They aren't really all that different. Also CSI is a general term whereas FSC is more specific to biology. That is why CSI (biology) was clarified. It isn't as if one thing can't have more than one term describing it. Do you think synonyms don't exist? How many different words and terms are there for having sex?

    Perhaps it would be good to show they are the 'same thing'.

    Read the OP.

    In three books- "No Free Lunch", "The Design Revolution" and "Signature in the Cell", both Dembski and Meyer make it clear:

    No Free lunch pages 148-49
    Biological specification always refers to function. An organism is a functional system comprising many functional subsystems. In virtue of their function, these systems embody patterns that are objectively given and can be identified independently of the systems that embody them. Hence these systems are specified in the same sense required by the complexity-specification criterion (see sections 1.3 and 2.5). The specification of organisms can be crashed out in any number of ways. Arno Wouters cashes it out globally in terms of the viability of whole organisms. Michael Behe cashes it out in terms of minimal function of biochemical systems. Darwinist Richard Dawkins cashes out biological specification in terms of the reproduction of genes. Thus, in The Blind Watchmaker Dawkins writes, “Complicated things have some quality, specifiable in advance, that is highly unlikely to have been acquired by random chance alone. In the case of living things, the quality is specified in advance is…the ability to propagate genes in reproduction.”

    Ooops, that may be too much for you to follow. In the paper "The origin of biological information and the higher taxonomic categories", Stephen C. Meyer wrote:

    Dembski (2002) has used the term “complex specified information” (CSI) as a synonym for “specified complexity” to help distinguish functional biological information from mere Shannon information--that is, specified complexity from mere complexity. This review will use this term as well.

    From SitC we have chapter 9 which is all about sequence specificity and functionality- all pertaining to CSI.

    And guess what? Functional sequence complexity is all about the sequence specificity required to produce a function.

    Both CSI (biology) and FSC refer to:

    Information means here the precise determination of sequence, either of bases in the nucleic acid or on amino acid residues in the protein.- Crick

     

  • At 9:32 PM, Blogger Joe G said…

    "Functioning proteins have a third independent requirement, the most important of all: their amino acids, like letters in a meaningful sentence, must link up in functionally specified sequential arrangements." Meyer, SitC, pg 207, pertaining to biological information/ SC/CSI (biology)

    Guess what functional sequence complexity pertains to?

     

  • At 9:45 PM, Blogger Joe G said…

    Why are there two different terms then?

    Two different football teams will most likely have some of the same plays but use different terminology to describe them. Two different armies fighting the same battle name the same battle differently (Shiloh/ North vs Pittsburg Landing/ South).

    Two different teams working on similar yet different issues with CSI being broader in usage/definition that FSC which pertains only to proteins.

     

  • At 5:29 PM, Blogger Jerad said…

    I agree there are frequently different terms or measures which are really targeted at the same quantity. I think feet and metres is a good metaphor. They both measure length or distance. But, as fixed metrics they have a constant conversion factor which can always be used to convert from one to the other. Then it's clear that the real difference is just a matter of units.

    What I am asking you to do is to show what the conversion factor or function is between the two metrics you reference. There would have to be one if they are measuring the same thing.

    (I do accept that for non-mathematical situations you're looking at something more like a translation dictionary but I think in the particular case we're discussing there should be an actual conversion factor or function.)

    I think it's unnecessary to point out that the conversion factor or function would have to be a one-to-one mapping otherwise it wouldn't work.

    Another analogy is temperature scales. Fahrenheit and Celsius have a known, fixed conversion factor. They are measuring the same thing and using one scale instead of another is strictly a matter of preference or ease of further conversions. Remember there is also the Kelvin scale.

    Angle measure can also be done in three major units: degrees, radian and gradians. I'm sure there are others.

    Mass, weight, work and many other quantities have multiple metrics. But there is always a conversion factor. What is the conversion factor for your two metrics?

     

  • At 6:01 PM, Blogger Joe G said…

    Again, the metrics have nothing to do with what I am saying.

    Both CSI (biology) and FSC pertain to the same functionally specified sequential arrangements- the definition of each term is the same.

     

  • At 4:11 AM, Blogger Jerad said…

    In the OP you said: "They are both measuring the same thing. If you have CSI (biology) it is because you have functional sequence complexity. And if you are measuring the FSC then you are measuring the CSI."

    I am just asking you to justify that. It should be really straight forward. Pick a couple of examples. Apply both metrics to both examples and show how the results using the two different methods can be reliably and unambiguously converted into each other. That will establish that they are measuring the same thing.

     

  • At 9:50 AM, Blogger Joe G said…

    If the definition is the same then yes, Jerad, they are measuring the same thing. The justification for that is the definition.

    Note I did not say that both have the same measurement technique nor that each technique reveals the same answer- it doesn't matter to my point which is about the DEFINITION of each term.

    That will establish that they are measuring the same thing

    No, Jerad, it won't. The DEFINITION says they are measuring the same thing.

     

  • At 10:10 AM, Blogger Jerad said…

    It should still be easy to work through a couple of examples to prove that what you say is correct. In case someone thought the definitions didn't match then you could show that they do.

    I don't see what the problem is, just work out some examples and prove your case.

     

  • At 10:22 AM, Blogger Joe G said…

    You are clueless. Even if one of the metrics is totally wrong it would not affect my argument. If someone thinks the definition is wrong then it is up to them to show it. Go ahead and try. You can contact the parties- Dembski, Meyer and Durston- and ask them

    My case is proven by the definition of the terms.

    The problem is that you don't seem to understand English

     

  • At 1:34 PM, Blogger Unknown said…

    Look, you claimed the two metrics measured the same thing. That's what you said. I'm just asking for some explanation and justification for that statement.

    The point being that definitions alone can be slippery and sometimes nebulous. It's better to check that they can be measured by a consistent standard. I'm just asking you to help put everything onto a rock-solid base.

    And I would say that you would have a problem if one of the metrics was 'totally wrong'. You need to pick your particular definition, your metric and show that those concepts are valid, consistent and repeatable. So when you say two of them are the same then it's fair to ask for justification.

    It's not up to me to contact the parties, I'm not the one making the claim. It's up to you to defend your position. And in this case that means upholding a claim you made.

    This is all very clear, I don't see why you're having such a problem with it.

     

  • At 9:48 PM, Blogger Joe G said…

    Look, you claimed the two metrics measured the same thing.

    And that means that CSI (biology) and FSC are one in the same. It doesn't mean the metrics are one in the same.

    And I would say that you would have a problem if one of the metrics was 'totally wrong'.

    You don't think that scientists and mathematicians never got anything wrong? Two people or teams working on the same problem and they both have to be right in order to move forward?

    You need to pick your particular definition, your metric and show that those concepts are valid, consistent and repeatable.

    Done. The definition is the same for both concepts- look up "synonym" and buy a vowel. FSC (Durston et al) has the more specific metric for its more specific use, so wrt proteins we would use it. And the rest is history, ie a done deal.

     

  • At 1:37 AM, Blogger Jerad said…

    I didn't say people never get things wrong but if you say they are measuring the same thing and one of them is wrong then I'd say you do have a problem. Which is why I've been asking for a couple of worked out examples.

    Can you at least show a couple of worked out examples for Durston's metric applied to proteins? You need to show how the method works in practice.

    And I think you still need to show/decide what you would use in other cases such as: genomes, interstellar signals, landscape features, etc.

     

  • At 6:14 AM, Blogger Joe G said…

    I didn't say people never get things wrong but if you say they are measuring the same thing and one of them is wrong then I'd say you do have a problem.

    I don't care what you say. What you say doesn't make any sense. If one person's metric is wrong then it gets discarded. What's the problem?

    Can you at least show a couple of worked out examples for Durston's metric applied to proteins? You need to show how the method works in practice.

    It's in the peer-reviewed paper that I have linked to several times when discussing measuring information- http://intelligentreasoning.blogspot.com/2014/04/measuring-csi-in-biology-repost.html

    And I think you still need to show/decide what you would use in other cases such as: genomes, interstellar signals, landscape features, etc.

    And I think you should focus on your own position as it is as lame as it gets. Metrics? Your position doesn't have any...

     

  • At 9:48 AM, Blogger Jerad said…

    Durston, et al's paper "Measuring the functional sequence complexity of proteins" is quite interesting. And they do work out a specific example. It is, as noted, restricted simply to proteins so that does limit its use and makes it harder to show that it's 'measuring the same thing.'

    I think you cannot say that the two metrics are measuring the same thing because I don't think Dr Dembski's CSI (as introduced in No Free Lunch) and the functional sequence complexity of Durston, et al are the same thing. And I think where they differ is where Dembski introduces 'specified'.

    What does 'specified' mean in this context? Dembski says "Specification depends on the knowledge of subjects. Is specification therefore subjective? Yes." (Page 66)

    As one reviewer put it: "the concept of "specified" is the point where Dembski injects the intelligent agent that he later "discovers" to be design! This makes the whole argument circular. Dembski wants "CSI" rather than a precise measure such as Shannon information because that gets the intelligent agent in. If he detects "CSI", then by his definition he automatically gets an intelligent agent. The error is in presuming a priori that the information must be generated by an intelligent agent."

    https://schneider.ncifcrf.gov/paper/ev/dembski/specified.complexity.html

    There is nothing subjective at all in the work of Durston, et al.

    I don't think the two metrics measure the same thing. And since no one uses Dr Dembski's metric (making it impossible to see if the two methods come close to giving consistently relatable results) and since Durston, et al's metric mentions nothing about intelligent design or 'specificity' I think referencing it gets you no where.

    Durston, et al's work does not give indication of design. And Dr Dembski's metric is flawed and used by no one. And unless you can prove that they are measuring the same thing (by working out some parallel examples and coming up with a conversion factor or function) then I'm afraid no amount of insisting they are the same will carry any weight. You gotta prove it because just thinking the definitions are the same isn't good enough. What are they both actually measuring? Are they really measuring the same thing? Not do you think they are but are they really? And they way to find out is to work some examples and compare the results.

     

  • At 10:14 AM, Blogger Joe G said…

    I think you cannot say that the two metrics are measuring the same thing because I don't think Dr Dembski's CSI (as introduced in No Free Lunch) and the functional sequence complexity of Durston, et al are the same thing.

    I don't care what you think. If one reads "No Free Lunch", "The Design REvolution" and "Signature in the Cell" and reasonable person can see that they are the same thing.

    What does 'specified' mean in this context?

    A sequence that produces a function.

    since Durston, et al's metric mentions nothing about intelligent design or 'specificity'

    Functional = specificity, Jerad.

    I don't think the two metrics measure the same thing.

    And yet I made the case that they do. And you have yet to address it.

    And unless you can prove that they are measuring the same thing

    I have

    (by working out some parallel examples and coming up with a conversion factor or function)

    Straw man

    You gotta prove it because just thinking the definitions are the same isn't good enough.

    I don't think they are the same. There isn't any doubt about it.

    And they way to find out is to work some examples and compare the results.

    That is your opinion and it doesn't hold any weight.

    So either you address my arguments or admit that you are just a bluffing idiot.

     

  • At 10:26 AM, Blogger Joe G said…

    From the paper:

    The measurement in Fits of the FSC provides significant information about how specific each monomer in the sequence must be to provide the needed/normal biofunction. The functional information measures the degree of challenge involved in searching the sequence space for a sequence capable of performing the function.

    There's the specificity, Jerad.

    Both CSI (biology) and FSC pertain to the sequence specificity required to produce functionality. And no one will ever be able to say otherwise and support it.

     

  • At 10:35 AM, Blogger Jerad said…

    I don't care what you think. If one reads "No Free Lunch", "The Design REvolution" and "Signature in the Cell" and reasonable person can see that they are the same thing.

    It doesn't mean those two metrics are measuring the same thing. Just because you or someone else says they are doesn't prove they are. You have to demonstrate it. Even if the definitions are the same it doesn't mean the metrics are measuring the same thing because there's no guarantee that the person who came up with the metric did it right. And you can't just say: yes they did, you have to show it.

    Functional = specificity

    Not really. Something can be specific without being functional.

    And yet I made the case that they do. And you have yet to address it.

    You just claimed it, you have to show that that is the case.

    I have

    You haven't proved anything. You've asserted something. That's not proof. You have to do more than just copy and paste things you think make good arguments. There is an equivalence here that needs to be demonstrated.

    I don't think they are the same. There isn't any doubt about it.

    I won't pick on you for an obvious mis-type.

    So either you address my arguments or admit that you are just a bluffing idiot.

    I am addressing your arguments. In my opinion the definitions of the two measures don't match so if you want to show they are measuring the same thing then you have to work some examples.

    This isn't the school yard where the most insistent person wins. Sometimes you have to do more than just insist. Sometimes you have to do some real mathematical work. Pick a protein, take the one used by Durston, et al, take their result, apply Dr Dembski's metric to the same protein, compare the results and see what you get.

    (Forgetting of course that you always insist that P{T|H) = 0 which, if true, would prove that the two metrics are NOT measuring the same thing. Best not get hoist by your own petard. But do remember that you have always, always, always insisted that P(T|H) = 0. You might want to reconsider that now because what do you get out of Dr Dembski's formula if you plug in 0 for P(T|H)?)

     

  • At 10:41 AM, Blogger Jerad said…

    There's the specificity, Jerad.

    Just because you found a use of the word 'specific' doesn't mean it's used in the same way as Dr Dembski used it.

    I get that you're avoiding doing any math but you really need to in order to prove your point. Like I said, even if both definitions were exactly the same you'd still need to show that both metrics are measuring the same thing.

    But the definitions and the functions are very different. So it's not clear if they are the same. So you have to prove they are. Not just just look for common words. There's no free lunch here.

     

  • At 10:53 AM, Blogger Joe G said…

    To form a protein, amino acids must link together to form a chain. Yet amino acids form functioning proteins only when they adopt very specific sequential arrangements, rather like properly sequenced letters in an English sentence. Thus, amino acids alone do not make proteins, any more than letters alone make words, sentences, or poetry. In both cases, the sequencing of the constituent parts determines the function (or lack of function) of the whole. Explaining the origin of the specific sequencing of proteins (and DNA) lies at the heart of the current crisis in materialistic evolutionary thinking. Meyer from http://www.discovery.org/a/200

    Just because you found a use of the word 'specific' doesn't mean it's used in the same way as Dr Dembski used it.

    By reading Dembski and Meyer and actually asking them, it is the same.

    I get that you're avoiding doing any math but you really need to in order to prove your point.

    Only an imbecile on an agenda thinks I need to do any math to prove the definition is the same.

    But the definitions and the functions are very different.

    No, they are not.

    If you have CSI (biology) it is because there is FSC- both refer to the specific sequence of amino acids that produce a function.

    So you have to prove they are.

    I have.

     

  • At 10:56 AM, Blogger Joe G said…

    Even if the definitions are the same it doesn't mean the metrics are measuring the same thing because there's no guarantee that the person who came up with the metric did it right.

    If CSI (biology) and FSC have the same definition (they do) then the metrics have to be measuring the same thing.

    This isn't the school yard where the most insistent person wins.

    Just follow the evidence- it proves that I am right. Heck you haven't even read the three books I referenced.

    Both CSI (biology) and FSC pertain to the sequence specificity required to produce functionality. And no one will ever be able to say otherwise and support it.

     

  • At 11:58 AM, Blogger Jerad said…

    If CSI (biology) and FSC have the same definition (they do) then the metrics have to be measuring the same thing.

    Well, since you think P(T|H) = 0 always then you're clearly incorrect that the metrics are measuring the same thing.

    What does Dr Dembski's metric give you if you replace P(T|H) with 0? You certainly don't get the results that Durston got for that protein.

    The metrics are NOT measuring the same thing. Even you think that they give different results because of your views on P(T|H). You can't get around this one. You quoted a paper where Durston used their metric on a protein. If you use Dr Dembski's metric on the same protein and you replace P(T|H) with 0 you will not get anything even close to the same result. You MIGHT get something vaguely compatible if you don't replace P(T|H) with 0 but I'll leave you to figure it out.

    Do you still think P(T|H) is always 0? Yes or no?

     

  • At 12:50 PM, Blogger Joe G said…

    Well, since you think P(T|H) = 0 always

    I don't think that. Mine was a SPECIFIC claim and it pertained to the evolution of ATP synthase and other protein machines by means of natural selection and drift. WRT to those, seeing there isn't any testable hypotheses, we can place a 0 there. How many times do I have to explain that to you?

    then you're clearly incorrect that the metrics are measuring the same thing.

    That is the equation for "specification" to see if it alone warrants a design inference.

    Dembski's CSI metric (No Free Lunch) was to show the limit, meaning anything above this number of bits is definitely designed. He used -log2(10^-150) for 500 bits in NFL but changed the 10^-150 to 10^-120 in subsequent papers pertaining to the UPB. 10^-120 would be about 400 bits. But again that is considering all of the resources in the universe, which we needn't do.

    What Durston et al., have done is show the amount of biological information in proteins is above Dembski's limit and as such are out of the reach of natural selection and drift.

    One metric, Dembski's in specification, is a yes/ no metric pertaining to the probability of natural selection and drift producing X. The other, Durston's, puts an actual number on it (the amount of biological information present).

    The amount of biological information, Durston, is an indication of whether or not life/ proteins/ protein machines ere designed. The result of Dembski's P(T|H) is an indication of whether or not life/ proteins/ protein machines were designed.

    Two different metrics measuring the same thing, the functional sequence complexity observed in an attempt to show if a designer was required or not.

     

  • At 2:12 PM, Blogger Joe G said…

    See also: Estimating the Probability of Functional Biological Proteins

     

  • At 4:58 PM, Blogger Jerad said…

    So, do you think there is a naturalistic hypothesis for the development of the protein (or the encoding of the protein in DNA) used by Durston in the cited paper? Do you think that P(T|H) for that protein is 0 or not? Durston's metric can be applied to that protein so I assume Dembski's metric can be as well. As you said, again: two different metrics measuring the same thing. So we should be able to apply them to the same things.

    If P(T|H) is 0 then what result do you get out of Dr Dembski's formula? How do you interpret that result as a yes or no pertaining to the probability of of natural selection and drift producing the protein? If P(T|H) is not 0 then what is it?

    If P(T|H) is all that is needed to determine if designed is required then why does Dr Dembski's formula include other terms? What is the purpose of those? What does phi-s(T) tell you? Why is there a log in the formula?

    By the way . . . what does 10^-150 or 10^-120 represent? They are very, very small numbers. Also, I note that in Dr Dembski's paper the term 10^-120 does not appear. 10^120 does appear. But it is multiplied by phi-s(T) and P(T|H).

     

  • At 7:57 PM, Blogger Joe G said…

    So, do you think there is a naturalistic hypothesis for the development of the protein (or the encoding of the protein in DNA) used by Durston in the cited paper?

    No, the probabilistic part of the equation is a general thing without a specific hypothesis.

    Do you think that P(T|H) for that protein is 0 or not?

    Can you point to a testable hypothesis for producing a protein from scratch or not?

    How do you interpret that result as a yes or no pertaining to the probability of of natural selection and drift producing the protein?

    If P(T|H) is a 0 then it is impossible for naturalistic processes to produce.

    If P(T|H) is all that is needed to determine if designed is required then why does Dr Dembski's formula include other terms?

    It's only if P(T|H) is 0 that we don't need anything else. What is 0 times anything else?

     

  • At 1:53 AM, Blogger Jerad said…

    So, since you think P(T|H) = 0 for the protein analysed by Durston, et al then Dr Dembski's formula comes down to:

    -log2(0)

    And what is that?

     

  • At 10:07 AM, Blogger Joe G said…

    Since you cannot posit any testable hypotheses for your position it isn't science- what is it?

     

  • At 11:48 AM, Blogger Unknown said…

    What is -log2(0)?

    You say both metrics measure the same thing so what does Dr Dembski's come out to be? How does that result compare to the one found by Durston, et al?

     

  • At 12:22 PM, Blogger Joe G said…

    What are your testable hypotheses?

    You say that your position is science yet you cannot say how to test its claims. If you can't say how to test the claims of your position then perhaps you should just stay off of discussion boards and blogs that discuss the matter.

     

  • At 12:55 PM, Blogger Unknown said…

    I am asking a question about a claim you made in the original post.

    Take the protein that Durston, et al use as an example in their paper. Apply Dr Dembski's metric to it (which makes sense since 'both metrics measure the same thing') and compare the results. It's not a matter of getting the same result since, as we agreed, you can have different units measuring the same quantity. But you should get comparable results. Durston, et al got a clear numerical result. What do you get out of Dr Dembski's metric?

    You are attempting to chance the subject, something which you would criticise someone else for.

    If you can't apply Dr Dembski's metric to the protein just admit it. But that's what it looks like when you try and divert the discussion. This is about a claim you made.

     

  • At 1:27 PM, Blogger Joe G said…

    Jerad, Dembski's is a probability calculation. If the P(T|H) is 0 then you don't need the rest of the equation and intelligent design is inferred. And Durston's numerical result concurs.

     

  • At 4:26 PM, Blogger Unknown said…

    I am still asking you a question about your original post.

    Dr Dembski no where implied that you could short-change his metric because one component of the calculation came out to be zero. AND he pretty clearly did not anticipate that P(T|H) = 0. He claimed that certain numerical results implied design. So what is your numerical result?

    And there is absolutely nothing in Durston's paper which even addresses design.

    So, again: Can you apply Dr Dembski's metric to the protein used as an example in Durston, et al and compare the results with theirs? How can you interpret Durston's result as supporting design based on what Durston says?

    AND if you short change Dr Dembski's result then can you say it's objective and quantitative? If you are just going to bail out at some point and claim design then how is that objective?

    Most importantly: what is Dr Dembski's metric applied to the protein used by Durston, et al? If they measure the same thing then you should get a result. What is the result? And what does Dr Dembski say about that result?

     

  • At 4:54 PM, Blogger Joe G said…

    Jerad, You are either very stupid or just on an agenda to obfuscate. Dembski's is a probabilistic formula. And if there isn't any probability then you don't use it, duh. And it doesn't matter what he anticipated. The fact remains that you and yours have failed to supply anything close to testable hypotheses for the claims of evolutionism.

    And yes, Dembski would concur that if P(T|H) is 0 and a specification exists then he would infer it was intelligently designed. He wanted to use his formula on a biological structure but admitted no one could provide P(T|H).

    The results are as I have stated. That isn't going to change. I linked to what Durston said- read it for yourself

     

  • At 1:38 AM, Blogger Jerad said…

    No where in Dr Dembski's paper does he discuss P(T|H) = 0, No where. So you just made that up.

    Your continuing to blame mainstream biologists for the failure of Dr Dembski's non-peer reviewed metric is childish. It's like you guys can just make up something and then blame others when it doesn't work. Is that how you do science then?

    And if no one can use it how can you declare that it measures the same thing as the derivation by Durston, et al? How can it measure anything if no one can use it?

    And, bottom line, you can't calculate Dr Dembski's metric ever let alone when you assume P(T|H) = 0.

    Until you can show that Dr Dembski's formula and that provided by Durston, et al give compatible results for the same examples you have not proven that they measure the same thing. It doesn't matter what anyone said the formulas were doing what matters is what they actually do.

     

  • At 6:38 AM, Blogger Joe G said…

    Jerad, Are you an imbecile? How could I make something up that is obviously true? Who cares what Dembski didn't talk about. The fact remains that neither you nor anyone else can produce a testable hypothesis wrt blind watchmaker evolution producing proteins, protein machines nor life.

    The blame is on evolutionists for their FAILURE to produce anything testable.

    Look Jerad, I made my case and all you can do is choke on it. It is clear that you cannot support the claims of your position and you think that reflects on IDists. You are a loser.

    What you say is meaningless. You are unable to form a coherent argument and you are unable to follow one.

    And BTW, I was not referring to Dembski's specification metric- never- that was all you, Joe and Patrick. The metric I was referring to, as I said, is in No Free Lunch.

    That said the formula in specification and Durston's are both a measure of the probability of naturalistic processes producing something, in this case a protein.

    But then again you are too stupid to understand that

     

  • At 9:06 AM, Blogger Jerad said…

    You cannot say that Dr Demski's metric measures the same thing as Durston's since you can't compute Dr Dembski's metric.

    It's Dr Dembski's fault if he created a metric that no one can use. It's not the fault of 150 years of evolutionary research. researchers like Durston, et al came up with their own metric, one that actually works.

    It is not true that Dr Dembski's metric returns a zero when you set P(T|H) = 0. If you could do the math you would know that. -log2(0) is not 0. After lots of exchanges you now claim you were looking at something else. Not that it matters since you can't compute that either.

    You're continual insistence that P(T|H) = 0 when you don't know what H is is also incorrect. If there is no H then P(T|H) has no value or meaning which is different than 0.

    Attacking someone else's position doesn't make your position more tenable, it just looks like you're trying to avoid dealing with the fact that you can't do the math.

     

  • At 9:23 AM, Blogger Joe G said…

    You cannot say that Dr Demski's metric measures the same thing as Durston's since you can't compute Dr Dembski's metric.

    Both metrics say that the proteins were designed. And no one knows how to test the claim that blind watchmaker processes didit.

    You lose.

    It's Dr Dembski's fault if he created a metric that no one can use

    It can be used. It's just that evos have failed to provide anything testable.

    t's not the fault of 150 years of evolutionary research

    BWAAAAAAAHAHAHAHAHAHAHAHAHA- 150 years of research and nothing that supports Darwin nor any of his surrogates.

    It is not true that Dr Dembski's metric returns a zero when you set P(T|H) = 0.

    I never said it did. Obviously you are just an asshole on an agenda.

    If there is no H then P(T|H) has no value or meaning which is different than 0.

    In what way?

    Attacking someone else's position doesn't make your position more tenable,

    Actually it does. Ya see, Jerad, science mandates design inferences first eliminate chance and necessity explanations. And tat is what I am doing.

    You do the math, asshole- tell us how many mutations it takes to produce a bacterial flagellum in a population that never had one. Oh, tat's right, your position doesn't have any math to support its unsupportable claims.

     

  • At 9:43 AM, Blogger Jerad said…

    Dr Dembski' metric doesn't say anything since you can't compute it. It's never been used because Dr Dembski devised something that couldn't be calculated.

    0 is a number. No meaning is not a number. The tan(pi/2) has no meaning. tan(pi) = 0. (tan(pi/2) does have a right and left limit but they are different and not numbers.)

    If you can't compute Dr Dembski's metric then you cannot say what it measures because it's not measuring anything.

     

  • At 9:59 AM, Blogger Joe G said…

    Jerad, You are obviously retarded. Just because you and yours have FAILed to provide anything doesn't mean Dembski's metric doesn't say anything. It says what we are investigating that doesn't have a testable hypothesis wrt naturalism can safely be inferred to have been intelligently designed.

    And again, if there isn't a testable hypothesis then P(T|H) is 0 and we just move on. We don't have anything to calculate and the design inference just falls out of the formula unmolested.

    Using Dembski's metric we see that ATP synthase is intelligently designed. And there isn't anything that you can do about it but whine and stomp your feet like a little child.

     

  • At 10:01 AM, Blogger Joe G said…

    But anyway, both metrics measure the probability of naturalistic processes producing the event, object or structure in question.

     

  • At 10:44 AM, Blogger Jerad said…

    Dr Dembski's metric can't say anything since it can't be computed. No where does he say that if you can't compute it therefore . . .

    Even if there were a lack of a naturalistic hypothesis that doesn't give you design. There are other options.

    P(T|H) is not zero. A probability of zero means something cannot happen. Even Dr Dembski admits that P(T|H) is not zero, it may be incredibly small but it's not zero.

    You can't use a metric you can't compute. Design does not just fall out. There'd be no point for the metric. Actually, there is no point to the metric: no one has ever used it and ID proponents have already made up their minds.

    And if you can't compute it then you cannot say it measures anything let alone the same thing as another metric.

     

  • At 11:18 AM, Blogger Joe G said…

    Yes, Jared, you are too stupid to understand simple explanations. I don't know why you think that means something.

    Even if there were a lack of a naturalistic hypothesis that doesn't give you design.

    See, you are retarded as I said a specification has to also be present. But then again the presence of a specification is why we were investigating in the first place.

    There are other options.

    Such as?

    P(T|H) is not zero.

    It depends on the case, of course. When it comes to blind watchmaker processes producing ATP synthase, well, that is quite impossible

    Even Dr Dembski admits that P(T|H) is not zero

    Liar

    You can't use a metric you can't compute.

    We can use it and we have.

    Design does not just fall out

    It does under the scenario I mentioned. Try to follow along.

    But anyway- you and yours have nothing. You don't have a methodology and you don't have any science. Bitching about ID isn't going to help you.

     

  • At 5:03 PM, Blogger Jerad said…

    If you want to blindly believe what people say they are doing without being able to check them then that is your choice. The fact is that no one, including you, has ever been able to compute Dr Dembski's metric for any real world example. So you cannot say that it measures anything. When you measure something you get a result.

    You can't use something you can't compute or evaluate. Unless you're a denialist who does no actual science.

    You and no one else has ever computed Dr Dembski's metric for any real world example. So it's useless and cannot be compared to other metrics.

    Durston, et al, proposed a metric and then showed that it could be computed for a particular, specific example. They did not mention design.

    The ID community thought they could hijack Durston's result and then claim that it was somehow equivalent to some non-peer reviewed metric that Dr Dembski published in various forms but that no one has ever computed.

    And instead of just denying everything as you usually do why not try and counter some of the specific things I am saying: show a worked out example of Dr Dembski's metric for any biological example. Show some kind of mathematical comparison between that result and what you get using Durston. Then, finally, make the argument that they are measuring the same thing. That's how you do science. It's hard work. It takes time.

    And if Dr Dembski couldn't come up with something that depended on people whose work he disagreed with well . . . that's pretty fucking stupid and pathetic. "I've got this great idea but because my opponents haven't done a certain kind of work you'll never know how great it is. It's their fault I'm not recognised as a genius."

    Durston, et al didn't look to ID for confirmation of their metric. They proposed one, they stated it explicitly, they computed it for a particular example. That's how you do science.

    Time to grow up.

     

  • At 5:18 PM, Blogger Jerad said…

    Seriously, you are saying: we have this great idea which proves blah, blah, blah but we can't actually compute it because you guys haven't established your case so we win.

    Why are you not using Dr Dembski's or Durston's metric and publicising the results? Why is that? You say you have used it . . . show me where and when. Give me a reference. A clear and explicit example not just something you think is using the same basic idea.

    Dr Dembski's metric has never been used. Prove me wrong.

    Durston's metric is not being used by ID proponents (curious if it's measuring the same thing eh?).

    You claim to have the high ground but you produce nothing. Why is that?

     

  • At 7:24 PM, Blogger Joe G said…

    Seriously, you are saying: we have this great idea which proves

    Seriously, you are demented.

    In order to reach a design inference you must first eliminate chance and necessity. And if no one, especially the dipshits who are pushing the chance and necessity model, can say how to test its claims, then yes we can say those type of explanations have been eliminated (for now- yes science is a tentative business- but you wouldn't know nor understand that). The next up is to see if a specification exists- biological function is the specification for Dembski, Meyer and Durston. Having eliminated the lame and observing a specification, we reach a design inference.

    Durston's metric is not being used by ID proponents (curious if it's measuring the same thing eh?).

    LoL! Durston is an ID proponent. See, you aren't reading what I post. You are just a belligerent asshole.

     

  • At 7:30 PM, Blogger Joe G said…

    If you want to blindly believe what people say they are doing without being able to check them then that is your choice.

    That is you, moron. The fact is no one, not even you, can say how to test the claims of evolutionism. You "argue" like a spoiled brat who has soiled himself and no one will change you.

    Durston is an IDist. It is safe to say all of the authors of that paper are. I know Abel is. Again- click here and read the article- and stop being such a douchebag.

    Dembski's metric has been used and it says that ATP synthase is intelligently designed. Prove me wrong- plug in the numbers and give it a go.

     

  • At 1:59 AM, Blogger Jerad said…

    No one is using Dr Dembski's metric, no one can compute it. You can't use it if you can't compute it. I HAVE computed -log2(0). Can you?

    ID proponents are not using Durston's metric which is curious if indeed it is measuring the same thing. Why is that? If the metric is ID friendly why isn't it being used?

    Until you can compare computed examples of the two metrics you cannot say they are measuring the same thing. You cannot just say because YOU think one of the terms in Dembski's metric is zero that you have computed the whole metric. Dr Dembski didn't just stop with P(T|H) did he? He should have because he had no idea of how to calculate it. The reason he hasn't referred to his metric again is because it turned out to be a dead end that NO ONE is using. Because they can't.

     

  • At 6:29 AM, Blogger Joe G said…

    Is 0 greater than, less than or equal to 10^-120? I ask because this is covered in Dembski's paper- the paper that you never read or couldn't comprehend.

    Durston is an ID proponent. He and others use his metric.

    I have explained why they measure the same thing. Your willful ignorance is neither and argument nor a refutation.

    And Dembski's metric is better than anything your position has.

    Is 0 greater than, less than or equal to 10^-120?

     

  • At 8:49 AM, Blogger Jerad said…

    0 is less than 10^-120, clearly. But a) there's more to the metric than that and b) P(T|H) is not actually equal to zero.

    But if P(T|H) = 0 then the metric says you have to compute -log2(0). Can you do that? Yes or no?

    Interesting that Durston thinks that evolution is a fact, at least what he calls microevolution.

    http://sandwalk.blogspot.co.uk/2015/07/the-two-mistakes-of-kirk-durston.html

    And he pretty clearly is, as you say, an ID proponent.

    https://powertochange.com/students/kirk/articles/popular-level-articles/a-scientific-case-for-intelligent-design-executive-summary/

    I didn't know that since I had only ever looked at that one paper. And it was published in a proper peer-reviewed journal. But the paper itself does not reference ID at all. So while he may have used some of the same procedures in other non-peer reviewed work it doesn't mean that his support of ID has been reviewed.

    It's a typical creationist ploy: say that something incredibly improbable must be designed. Nothing new here.

     

  • At 9:37 AM, Blogger Joe G said…

    Interesting that Durston thinks that evolution is a fact, at least what he calls microevolution.

    ID isn't anti-evolution, moron.

    And look, dipshit, there aren't any papers referencing natural selection producing proteins or protein machines. That means nothing evolutionism claims is in peer-review.

    It's an ignorant and cowardly lie to say ID says something is designed just because it is incredibly improbable. With you it is willful ignorance as I have told you the opposite.

    And P(T|H) = 0 until you and yours can demonstrate otherwise. Good luck with that

     

  • At 11:18 AM, Blogger Unknown said…

    ID is anti-evolution since it declares that natural processes are inadequate. You mean that ID isn't anti-common descent but that does depend on which version of ID you believe in.

    Dr Dembski's arguments essentially come down to: it's too improbable therefore it's designed. His 2005 paper is really saying that. It doesn't matter what you say, what matters is what Dr Dembski's metric actually measures and it comes down to improbability upon which he sets an arbitrary limit. It's clear if you understand the mathematics.

    P(T|H) is not zero as there is always a chance, even if it's very small, of a biological structure developing though unguided naturalistic processes. And then you'd have to determine phi-s(T) which you cannot do. So you decide that P(T|H) is zero.

    And even if it was zero then you'd still have to compute -log2(0) which is easy if you understand the mathematics. Can you compute -log2(0)? You keep not answering that question. I think that means you can't do it. Because you always ignore questions you can't answer. As if they'll go away.

    Figured out the relative cardinality of the primes yet?

     

  • At 4:45 PM, Blogger Joe G said…

    ID is anti-evolution since it declares that natural processes are inadequate

    There is only one definition of evolution that posits naturalistic processes. And it is a non-scientific definition.

    Dr Dembski's arguments essentially come down to: it's too improbable therefore it's designed.

    Only to a moron who cannot comprehend what Dembski has written.

    Look, dipshit, the only reason we are talking about probabilities is because your position doesn't have anything- no testable hypotheses, no models, no science.

    If your position had something we wouldn't be talking about probabilities, we would be talking about that.

     

  • At 5:04 PM, Blogger Unknown said…

    Oh look, you dodged every question again. Typical.

    IF P(T|H) = 0 then what is -log2(0)? That's what Dr Dembski's metric says you have to compute. So what is it?

    You clearly are in a bad position to say what Dr Dembski actually wrote since you can not do the math required.

    We are talking about some metrics that you brought up. One of which has never been computed because Dr Dembski chose to include terms he didn't know how to evaluate. And you blame people who never supported or agreed with Dr Dembski's position. Whine, whine, whine.

    Show us how you can evaluate Dr Dembski's metric. Show us how you can use Durston's metric. Do something. Do some work. You made some claims, back them up.

    Or keep ignoring questions you can't answer. Like usual.

     

  • At 5:08 PM, Blogger Unknown said…

    What is -log2(0)?

    You can't figure that out can you?

     

  • At 5:37 PM, Blogger Joe G said…

    If P(T|H) is zero and a specification exists then design is inferred. In the paper Dembski shows you how to use his metric when P(T|H) isn't zero.

    Look, dipshit, the only reason we are talking about probabilities is because your position doesn't have anything- no testable hypotheses, no models, no science.

    If your position had something we wouldn't be talking about probabilities, we would be talking about that.

     

  • At 1:33 AM, Blogger Jerad said…

    Too funny, you denied that Dr Dembski's argument was really just: if something is too improbable and it has a specification (which is only in the eyes of the beholder) then it was designed and yet that is exactly the argument you just made.

    So where does Dr Dembski say what to do when P(T|H) = 0 or did you just make that up? I think you're thinking: zero is less than 2-whatever so that's good enough, it's completely improbable therefore designed. But P(T|H) isn't zero just because you can't find an H. That is just not right. And no matter how many times you insist it is doesn't make it so. It's just you stamping your feet and saying you won when you can't even do the math in Dr Dembski's formula. If you could and you tried using P(T|H) = 0 you could see that.

    By the way, -3 is also less than the threshold value. Can you use that in the formula? If you could do the math you could find out.

    You can't evaluate -log2(0). Too funny.

     

  • At 7:27 AM, Blogger Joe G said…

    Biological function isn't just in the eye of the beholder, moron.

    So where does Dr Dembski say what to do when P(T|H) = 0 or did you just make that up?

    He doesn't have to say anything. If yours is impossible then it is eliminated. Duh.

    But P(T|H) isn't zero just because you can't find an H

    Sure it is and nothing you can say will change that.


    Look, dipshit, the only reason we are talking about probabilities is because your position doesn't have anything- no testable hypotheses, no models, no science.

    If your position had something we wouldn't be talking about probabilities, we would be talking about that.

     

  • At 9:15 AM, Blogger Jerad said…

    Biological function isn't just in the eye of the beholder, moron.

    They way you determine specificity it is.

    He doesn't have to say anything. If yours is impossible then it is eliminated. Duh.

    But it's not impossible. It's just you saying it is. Doesn't make it true. It maybe very, very improbable but it's not impossible.

    Sure it is and nothing you can say will change that.

    Gee, I thought people who do science always admit they will change their mind if new data arises. Just not you though.

    And you can't evaluate -log2(0). Too funny. The great scientist who can't do elementary mathematics.

    That means you couldn't evaluate Dr Dembski's metric if P(T|H) was something other than zero. Because you don't know how to take a log base 2. So there is absolutely no way you could ever compare results from the two metrics. You can't even compute one of them.

    And you can't find the relative cardinality of the primes so you can't even support your own ideas.

     

  • At 9:46 AM, Blogger Joe G said…

    They way you determine specificity it is.

    No, Jerad, biological function is an observation that can be repeated and confirmed via experiments.

    But it's not impossible

    You cannot demonstrate any probability

    Gee, I thought people who do science always admit they will change their mind if new data arises.

    Yes and if you and yours ever come up with something we will take a look. You would have a better chance showing that Stonehenge was the result of non-telic processes.


    Look, asshole, your position doesn't even deserve a place at probability discussions. Don't blame me for your failures. Grow up already

     

  • At 4:40 PM, Blogger Unknown said…

    You look at some biological structure which performs some particular function and say: ooo, how improbable is that? What you should be asking is: what is the probability of some functiion arising?

    The classic lottery example is pertinent. If you take a particular example of Joe Bloggs winning a lottery on some particular day having bought a ticket from some particular location then, yes, the chances of that happening are vanishingly small. But what are the chances of somebody, somewhere, winning the lottery at some time?

    Specificity is a dead issue because it draws the target around a bullet hole instead of asking what is the chance of some bullet hitting something.

    And you cannot calculate any probability. You just claim one is zero and avoid proving that you cannot calculate the log base 2 of some value. You can't do that calculation can you? As you have continually demonstrated in this thread you are too much of a coward to even adress the issue.

    You pretend to be scientific when you've already made up your mind and are closed to anything which counters your view. As you've shown time and time again. You deny anything which casts any doubt on your stance.

    You can't do high school level mathematics like finding the logarithm base 2 of some value. You are in no position to judge any real scientific research since you can't do the math. As you've shown time and time again.

    And you can't back up your own claim about relative cardinalities. Something you just made up with no academic support whatsoever.

    Prove me wrong: find the log base 2 of 20 and 0. Let's see your ability.

     

  • At 11:03 PM, Blogger Joe G said…

    You look at some biological structure which performs some particular function and say: ooo, how improbable is that?

    Not me. I look at biology and say only a complete fool would think that blind and mindless processes could produce this. Then I look around and find that those people exist and true to form they cannot support their position.

    Look, dipshit, the only reason we are talking about probabilities is because your position doesn't have anything- no testable hypotheses, no models, no science.

    If your position had something we wouldn't be talking about probabilities, we would be talking about that.

     

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