[QUOTE=wickedplayer494;44094736]For fuck's sakes, it isn't even an article dealing with politics. If it was, then you'd have reason to bitch about Fox News.[/QUOTE]
Well I mean science isn't exactly their best subject either.
[QUOTE=Swebonny;44094719]I'm not sure how it exactly works, so I'm just speculating right now. But even though the quality of an article is lacking and isn't peer reviewed, an incautious person may still reference it in their scientific works. And that could potentially cause a chain of bad papers.
Peer-reviewed journals can shit out irrelevant bullshit as well, so peer-review doesn't always imply that the information in the paper is valid. And it's also what the people behind: [URL]http://pdos.csail.mit.edu/scigen/[/URL] tries to show. If you scroll down you'll find several stories about people using the generator to create "papers" that gets accepted to what seems to be respectable journals.
In conclusion, I don't think they should be seen as irrelevant, but should be taken with a grain of salt, and several scoops of salt if it claims something groundbreaking.[/QUOTE]
Some journals claim to peer review with great scrutiny but in actuality will accept anything that's submitted; especially some open access journals when you bundle your submission with a lovely cash incentive.
[QUOTE=Jabberwocky;44096977]Some journals claim to peer review with great scrutiny but in actuality will accept anything that's submitted; especially some open access journals when you bundle your submission with a lovely cash incentive.[/QUOTE]
Is that so?
[QUOTE=Sableye;44094568]i remember seeing one as an example in one of my classes,
it was about some new mathmatical formula for finding the area under a linear curve,
LITTERALLY someone wrote about how they discovered a mathmatical way to find the area under a curve accurately and it was like 3 pages of giberish, then in the peer comments just one sentence
this is just integration[/QUOTE]
[URL]http://care.diabetesjournals.org/content/17/2/152.full.pdf+html[/URL]
And it's fucking hilarious. It's basically biologists being biologists and forgetting that mathematics exists beyond approximations and guesswork.
thats the one
[QUOTE=sltungle;44097447][URL]http://care.diabetesjournals.org/content/17/2/152.full.pdf+html[/URL]
And it's fucking hilarious. It's basically biologists being biologists and forgetting that mathematics exists beyond approximations and guesswork.[/QUOTE]
Because it's totally possible to integrate data sets.
[QUOTE=Falubii;44097799]Because it's totally possible to integrate data sets.[/QUOTE]
Sorry, I guess this is still technically an approximation however it's a much better one than the one they were apparently using before hand and it's still been known for hundreds of years anyway.
You can actually integrate data sets, though - sort of. If you have N data points just tell the computer to plot a line of fit of order N-1 and integrate the resulting polynomial. Of course depending on how 'far apart' your data points are the answer you get might not be entirely meaningful, but if that's the case you shouldn't be bothering to find the area underneath your curve in the first place because it's apparently not very good data.
And obviously as N gets bigger the computing time required to find a polynomial of best fit can quite quickly get out of hand, but if your data sets are that large then you're not going to be going out of your way to use the trapezoid approximation, are you? The computer will find a polynomial to fit your data quicker than you can draw out all of those trapezoids and compute their area.
[QUOTE=sltungle;44097904]Sorry, I guess this is still technically an approximation however it's a much better one than the one they were apparently using before hand and it's still been known for hundreds of years anyway.
You can actually integrate data sets, though - sort of. If you have N data points just tell the computer to plot a line of fit of order N-1 and integrate the resulting polynomial. Of course depending on how 'far apart' your data points are the answer you get might not be entirely meaningful, but if that's the case you shouldn't be bothering to find the area underneath your curve in the first place because it's apparently not very good data.
And obviously as N gets bigger the computing time required to find a polynomial of best fit can quite quickly get out of hand, but if your data sets are that large then you're not going to be going out of your way to use the trapezoid approximation, are you? The computer will find a polynomial to fit your data quicker than you can draw out all of those trapezoids and compute their area.[/QUOTE]
The paper might not be profound, but it wasn't describing integration. It wasn't even a Riemann sum because of the inconsistency of time intervals. And no you can't integrate data sets, you can approximate them. You really can't integrate anything that is discrete.
If you look at the date of publication, it becomes clear why this might be useful. In 1994 it's conceivable that many clinics that would be looking at this blood work didn't have computer programs to calculate these results, and this was just a bit of a brush up for some doctors so they can easily compute these areas.
[quote]created by nothing more than an automated word generator that puts random, fancy-sounding words together in plausible sentence structures[/quote]
yes that is the definition of a student, i don't see the problem here
I don't see this being an issue for the higher standards publishers. My publishing was in a review-update cycle for almost a full year before they declared it fit to be published. Most of my mentors and professors say they experience the same.
[QUOTE=x-quake;44099151]I don't see this being an issue for the higher standards publishers. My publishing was in a review-update cycle for almost a full year before they declared it fit to be published. Most of my mentors and professors say they experience the same.[/QUOTE]
[QUOTE=Bradyns;44089128]What journals were they published in though? Hard science journals?
There are a lot of 'established journals' which are bunk.
I doubt you'd see something like this in 'Science'.[/QUOTE]
[url=http://www.chemistry-blog.com/2013/08/13/alleged-data-manipulation-in-nano-letters-and-acs-nano-from-the-pease-group/]It can happen[/url].
[img]http://www.chemistry-blog.com/wp-content/uploads/2013/08/1.png[/img]
And here's the [url=http://pubs.acs.org/doi/abs/10.1021/nl400959z]now-withdrawn paper from JACS[/url] (for the lazy: [url=http://pubs.acs.org/doi/suppl/10.1021/nl400959z/suppl_file/nl400959z_si_003.pdf]paper proper[/url], [url=http://pubs.acs.org/doi/suppl/10.1021/nl400959z/suppl_file/nl400959z_si_002.pdf]supporting info with the sketch images[/url]). The author even had the gall to threaten the bloggers with libel.
[QUOTE=sltungle;44097904]Sorry, I guess this is still technically an approximation however it's a much better one than the one they were apparently using before hand and it's still been known for hundreds of years anyway.
You can actually integrate data sets, though - sort of. If you have N data points just tell the computer to plot a line of fit of order N-1 and integrate the resulting polynomial. Of course depending on how 'far apart' your data points are the answer you get might not be entirely meaningful, but if that's the case you shouldn't be bothering to find the area underneath your curve in the first place because it's apparently not very good data.
And obviously as N gets bigger the computing time required to find a polynomial of best fit can quite quickly get out of hand, but if your data sets are that large then you're not going to be going out of your way to use the trapezoid approximation, are you? The computer will find a polynomial to fit your data quicker than you can draw out all of those trapezoids and compute their area.[/QUOTE]
Lagrange interpolations, if that's what you were talking about, can actually be quite inaccurate as there is no limit to the difference between the polynomial and the approximated function. If you're shooting for precision you would be better off using the trapezoid method, or better yet, Simpson's rule.
[QUOTE=Cakebatyr;44099291][url=http://www.chemistry-blog.com/2013/08/13/alleged-data-manipulation-in-nano-letters-and-acs-nano-from-the-pease-group/]It can happen[/url].
[img]http://www.chemistry-blog.com/wp-content/uploads/2013/08/1.png[/img]
And here's the [url=http://pubs.acs.org/doi/abs/10.1021/nl400959z]now-withdrawn paper from JACS[/url] (for the lazy: [url=http://pubs.acs.org/doi/suppl/10.1021/nl400959z/suppl_file/nl400959z_si_003.pdf]paper proper[/url], [url=http://pubs.acs.org/doi/suppl/10.1021/nl400959z/suppl_file/nl400959z_si_002.pdf]supporting info with the sketch images[/url]). The author even had the gall to threaten the bloggers with libel.[/QUOTE]
I certainly maintain that there can be issues in manipulated data as in the case you posted.
This being said, I believe the articles in the op are essentially on a different level. If the articles went through peer-review at all before being published, someone should have noticed something was wrong. They either didn't review them or the reviewers were incompetent.
[QUOTE=Falubii;44097986]The paper might not be profound, but it wasn't describing integration. It wasn't even a Riemann sum because of the inconsistency of time intervals. And no you can't integrate data sets, you can approximate them. You really can't integrate anything that is discrete.
If you look at the date of publication, it becomes clear why this might be useful. In 1994 it's conceivable that many clinics that would be looking at this blood work didn't have computer programs to calculate these results, and this was just a bit of a brush up for some doctors so they can easily compute these areas.[/QUOTE]
Yeah except she call's it Tai's model and it's literally just the trapezoidal rule lol
[editline]2nd March 2014[/editline]
This is investigated succinctly and in depth in a response paper:
[url]http://www.ncbi.nlm.nih.gov/pubmed/7677819[/url]
[QUOTE=JohnnyMo1;44101643]Yeah except she call's it Tai's model and it's literally just the trapezoidal rule lol[/QUOTE]
But isn't the trapezoid rule method of evaluating a Riemann sum?
[QUOTE=Falubii;44101660]But isn't the trapezoid rule method of evaluating a Riemann sum?[/QUOTE]
It's an approximation method.
[QUOTE=Falubii;44097986]The paper might not be profound, but it wasn't describing integration. It wasn't even a Riemann sum because of the inconsistency of time intervals. And no you can't integrate data sets, you can approximate them. You really can't integrate anything that is discrete.
If you look at the date of publication, it becomes clear why this might be useful. In 1994 it's conceivable that many clinics that would be looking at this blood work didn't have computer programs to calculate these results, and this was just a bit of a brush up for some doctors so they can easily compute these areas.[/QUOTE]
computers in 1994 were powerful enough to do best fit curves, this was just biologists being dumb, analyzing data was what computers had been around since the 50s to do, they completely had enough power to find this
[editline]2nd March 2014[/editline]
the problem with this word generator is people use too much jargon that it appears to be understandable even if it's gibberish. its a problem in the scientific community as a whole to over jargonize their stuff and now someone has deviously called them on it.
[QUOTE=Sableye;44103595]computers in 1994 were powerful enough to do best fit curves, this was just biologists being dumb, analyzing data was what computers had been around since the 50s to do, they completely had enough power to find this
[editline]2nd March 2014[/editline]
the problem with this word generator is people use too much jargon that it appears to be understandable even if it's gibberish. its a problem in the scientific community as a whole to over jargonize their stuff and now someone has deviously called them on it.[/QUOTE]
It's for medical clinics doing applied work, not some long term study. I'm sure not every clinic in 1994 had the required software for the calculations. You seem eager to bash biologists.
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