When experimental results appear that can't be explained, they're often discounted as being useless. The researchers might say that the experiment was designed badly, the equipment faulty, and so on.
It may indeed be the case the faults occurred, but it could also be the case when consistent information emerges, but these possibilities are rarely investigated when the data agrees with pre-existing assumptions, leading to possible biases in how data is interpreted.
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I was particularly interested to read that breakthroughs were most likely to come from group discussions:
"While the scientific process is typically seen as a lonely pursuit — researchers solve problems by themselves — Dunbar found that most new scientific ideas emerged from lab meetings, those weekly sessions in which people publicly present their data. Interestingly, the most important element of the lab meeting wasn’t the presentation — it was the debate that followed. Dunbar observed that the skeptical (and sometimes heated) questions asked during a group session frequently triggered breakthroughs, as the scientists were forced to reconsider data they’d previously ignored. The new theory was a product of spontaneous conversation, not solitude; a single bracing query was enough to turn scientists into temporary outsiders, able to look anew at their own work."
Although it turns out that discussion with people from a diverse range of people is most important - having a room full of people who share assumptions and expertise tends not to lead to creative scientific insights.