Genetic Engineering and Other Factors That Might Affect Human-Animal Interactions in the Research Setting
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
Evidence exists, particularly in the welfare literature of nonhuman animals on the farm, that the interaction between nonhuman animals and the personnel who care for them can have a strong effect on the animals' behavior, productivity, and welfare. Among species commonly used for biomedical research, mice appear to be the least-preferred species in animal care facilities. A review of the literature and observations of animal care staff interacting with mice indicated that the following factors may influence this: their small size, their particular behavioral characteristics, and husbandry constraints (such as housing in ventilated racks). In addition, this study questioned whether animal care personnel have a different perception of genetically engineered animals and whether this, in turn, has an effect on their interactions with these animals. The ability to carefully observe an animal's behavior is key in carrying out an animal-wellness assessment and in minimizing pain and distress. Attention to human-animal interactions in the research setting represents an opportunity for refinement for large numbers of animals and potentially for reduction of animal use.
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 | 0.004 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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