Bibliographic record
Abstract
During the years that have passed since the first and second version of the Declaration, and until the fifth version in 2001, biomedical research has expanded its universe considerably.Not only medical doctors now participate as scientists in projects.Many more disciplines are now represented: biochemists, psychologists, nurses, geneticists, physiotherapists and many others have ) fortunately ) entered the scene.Besides, the levels of scientific approaches in biomedicine have widened and now span from molecular biology to large-scale epidemiology, and so have the research subjects from individual patients to pedigrees in clinical-genetic research.Furthermore, a geographical globalization has taken place, meaning that trans-national projects, also including cooperation between developing and developed countries, have been much more prevalent.These developments since the Declaration's first versions also mean that the spectrum of research ethical demands to projects involving man has widened considerably, even more than is covered by the fifth version of the Declaration.Instead, some of the extended demands have been covered by a large number of new research ethical codes, of which some even contradict each other.The presentation will conclude with suggestions to scientists and research ethical control bodies how to rank the different codes and how to select the appropriate number for concrete projects.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.468 | 0.289 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".