lol you are tripping w all the Mohammad obsession. I did not know that you were a black poster.. and I don't think ur a c00n, so I won't diss u any longer.Well, if you don't know the difference between 'to' and 'too' of course what I posted would be over your head.
You should. Insults are more effective when you don't look like a doofus.
No. You're in denial, you have no evidence to prove your assertion, and I keep calling you on your bullshyt.
I could care less about what you consider a diss. Also, all the evidence is conclusive that I am neither female nor non-'Black'. You, on the other hand, are a fool who believes nonsense.
Mohammad liked to wear girl's clothing.
I will just leave u w some info.
Peace
Other data-heavy disciplines face similar challenges. Models which can be “tuned” in many different ways give researchers more scope to perceive a pattern where none exists. According to some estimates, three-quarters of published scientific papers in the field of machine learning are bunk because of this “overfitting”, says Sandy Pentland, a computer scientist at the Massachusetts Institute of Technology.
Similar problems undid a 2010 study published in Science, a prestigious American journal (and reported in this newspaper). The paper seemed to uncover genetic variants strongly associated with longevity. Other geneticists immediately noticed that the samples taken from centenarians on which the results rested had been treated in different ways from those from a younger control group. The paper was retracted a year later, after its authors admitted to “technical errors” and “an inadequate quality-control protocol”.
The number of retractions has grown tenfold over the past decade. But they still make up no more than 0.2% of the 1.4m papers published annually in scholarly journals. Papers with fundamental flaws often live on. Some may develop a bad reputation among those in the know, who will warn colleagues. But to outsiders they will appear part of the scientific canon.
Blame the ref
The idea that there are a lot of uncorrected flaws in published studies may seem hard to square with the fact that almost all of them will have been through peer-review. This sort of scrutiny by disinterested experts—acting out of a sense of professional obligation, rather than for pay—is often said to make the scientific literature particularly reliable. In practice it is poor at detecting many types of error.
John Bohannon, a biologist at Harvard, recently submitted a pseudonymous paper on the effects of a chemical derived from lichen on cancer cells to 304 journals describing themselves as using peer review. An unusual move; but it was an unusual paper, concocted wholesale and stuffed with clangers in study design, analysis and interpretation of results. Receiving this dog’s dinner from a fictitious researcher at a made up university, 157 of the journals accepted it for publication.
Dr Bohannon’s sting was directed at the lower tier of academic journals. But in a classic 1998 study Fiona Godlee, editor of the prestigious British Medical Journal, sent an article containing eight deliberate mistakes in study design, analysis and interpretation to more than 200 of the BMJ’s regular reviewers. Not one picked out all the mistakes. On average, they reported fewer than two; some did not spot any.
Another experiment at the BMJ showed that reviewers did no better when more clearly instructed on the problems they might encounter. They also seem to get worse with experience. Charles McCulloch and Michael Callaham, of the University of California, San Francisco, looked at how 1,500 referees were rated by editors at leading journals over a 14-year period and found that 92% showed a slow but steady drop in their scores.
As well as not spotting things they ought to spot, there is a lot that peer reviewers do not even try to check. They do not typically re-analyse the data presented from scratch, contenting themselves with a sense that the authors’ analysis is properly conceived. And they cannot be expected to spot deliberate falsifications if they are carried out with a modicum of subtlety.
Fraud is very likely second to incompetence in generating erroneous results, though it is hard to tell for certain. Dr Fanelli has looked at 21 different surveys of academics (mostly in the biomedical sciences but also in civil engineering, chemistry and economics) carried out between 1987 and 2008. Only 2% of respondents admitted falsifying or fabricating data, but 28% of respondents claimed to know of colleagues who engaged in questionable research practices.
Peer review’s multiple failings would matter less if science’s self-correction mechanism—replication—was in working order. Sometimes replications make a difference and even hit the headlines—as in the case of Thomas Herndon, a graduate student at the University of Massachusetts. He tried to replicate results on growth and austerity by two economists, Carmen Reinhart and Kenneth Rogoff, and found that their paper contained various errors, including one in the use of a spreadsheet.