Bibliographic record
Abstract
The fifth revision of the 1964 Declaration of Helsinki, published in October 2000, sets out international standards for conducting medical research with human subjects.1 Revisions of this or any other research ethics code are unlikely to make research more ethical throughout the world, however, without some means of strengthening capacity to promote and implement such standards. Strengthened capacity in research ethics is needed in both developed and developing countries, though the need is particularly acute in developing countries. A recent Washington Post investigation into research in developing countries revealed “a booming, poorly regulated testing system that is dominated by private interests and that far too often betrays its promises to patients and consumers.”2 Research in developing countries was a flash point of the fifth revision of Helsinki because the declaration retains the requirement that new treatments should be tested against the “best current” treatment. Critics argue that this standard does not allow the testing of low cost, sustainable treatments, such as aspirin for coronary artery disease, which might yield substantial health improvements in developing countries but …
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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 | 0.319 | 0.214 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.065 |
| Scholarly communication | 0.028 | 0.025 |
| Open science | 0.007 | 0.018 |
| Research integrity | 0.032 | 0.056 |
| Insufficient payload (model declined to judge) | 0.006 | 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".