I disagree strongly. Researchers are reporting results as if they actually demonstrate the existence of phenomena, often leading others to pursue that line of research and sometimes leading to clinical trials. They're doing so based on underpowered studies and statistical procedures that are guaranteed to produce lots of false positives. They don't have to be doing that.
Even proper studies with statistically significant and solid numbers can still lead to a conclusion that turns out to be false. My experience is more in the fields of immunology and microbiology where we are often working with a big black box, or a bowl of spaghetti, whichever metaphor you would prefer. It is nearly impossible to decipher the entire host-pathogen relationship in a single study. You have to do it in bits across many different research labs. At times, certain interactions will look very promising, but upon further study they aren't important. Perhaps your field is a bit different.
We don't have to wait until we're 100% sure; physicists don't. But they don't get two thirds of their results wrong, either.
What do you mean by "wrong"? Do you mean that the reported data is wrong because of experimental error, the data is analysed incorrectly, or that the conclusions drawn from the data are incorrect/not supported?
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