Researchers, animal support and regulatory staff: symbiosis or antagonism?
Bibliographic record
Abstract
Animals are studied en masse by biologists around the world in a variety of biomedical and basic research studies. All this research benefits humankind and animals alike as it tackles a wide variety of problems ranging from those of conservation biology to medicine. Research with animal subjects is a complex endeavor that requires the cooperation and collaboration of a large number of experts, from the principal investigator through technicians and vivarium staff to regulatory experts. The research must be conducted in a humane manner that adheres to acceptable practices regulated by local, state and federal guidelines, rules and the law. In this short opinion article, we examine the current state of affairs regarding how researchers, animal support staff and regulatory experts work together. We pay particular attention to potential conflicts that may arise from the occasionally distinct roles played by those involved in animal research, and we provide some suggestions as short- and long-term remedies that have not been previously discussed in the literature.
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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 | 0.140 | 0.134 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.034 |
| Scholarly communication | 0.021 | 0.018 |
| Open science | 0.004 | 0.020 |
| Research integrity | 0.016 | 0.018 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".