Incorporating Laboratory Animal Science into Responsible Biomedical Research
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Biomedical research has made great strides in the past century leading to rapid advances in human life expectancy, all derived from improved understanding, prevention, and treatment of many diseases and conditions. Research involving laboratory animals has played a significant role in this medical progress. However, there continues to be controversy surrounding the use of animals in research, and animal models have been questioned regarding their relevance to human conditions. While research fraud and questionable research practices could potentially contribute to this problem, we argue that a relative ignorance of laboratory animal science has contributed to the "uncontrolled vivarium experiment" that runs parallel to the more controlled scientific experiment. Several variables are discussed, including husbandry, animal environment, social housing, and more, that can contribute to this uncontrolled experiment, and that can simultaneously decrease quality of life for rodent test subjects when ignored. An argument is put forward that laboratory animal veterinarians and scientists can and should play an important role in better controlling such variables. Similarly, the laboratory animal veterinarian and scientist should play an important role in responsible science by addressing complex interdisciplinary challenges.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 it