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
Human and animal research both operate within established standards. In the United States, criticism of the human research environment and recorded abuses of human research subjects served as the impetus for the establishment of the National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research, and the resulting Belmont Report. The Belmont Report established key ethical principles to which human research should adhere: respect for autonomy, obligations to beneficence and justice, and special protections for vulnerable individuals and populations. While current guidelines appropriately aim to protect the individual interests of human participants in research, no similar, comprehensive, and principled effort has addressed the use of (nonhuman) animals in research. Although published policies regarding animal research provide relevant regulatory guidance, the lack of a fundamental effort to explore the ethical issues and principles that should guide decisions about the potential use of animals in research has led to unclear and disparate policies. Here, we explore how the ethical principles outlined in the Belmont Report could be applied consistently to animals. We describe how concepts such as respect for autonomy and obligations to beneficence and justice could be applied to animals, as well as how animals are entitled to special protections as a result of their vulnerability.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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