Bibliographic record
Abstract
Publisher Summary This chapter presents patterns of discovery that illuminate some of the most important developments in the history of medicine. Four different kinds of hypotheses employed in medical discovery that includes hypotheses about basic biological processes relevant to health and hypotheses about the causes of disease are explained. Hypotheses about treatment of disease based on traditional imbalance theories, for example, the use in Hippocratic medicine of bloodletting to balance humors, have been popular but unsubstantiated. On the neuroscience view of mental representation, a concept is a pattern of neural activity, so concept formation and reorganization are neural processes. In the development of the bacterial theory of ulcers, initial formation by Warren of the concept of spiral gastric bacteria seems to have been both perceptual and cognitive. Psychological patterns of discovery include the development of new hypotheses by questioning, search, and causal reasoning, and the development of new concepts by combining old ones. Research in the burgeoning field of cognitive neuroscience is making it possible to raise, and begin to answer, questions about the neural processes that enable scientists to form hypotheses and generate concepts.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.004 | 0.015 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.021 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".