A rating scale for wildness and ease of handling laboratory mice: results for 21 inbred strains tested in two laboratories
Bibliographic record
Abstract
Rating scales for difficulty in capturing and holding mice were devised that proved to be easy to use and highly sensitive to differences among mouse strains on the A and B priority lists of the Mouse Phenome Project. The simplicity of the scales makes it feasible to rate wildness during behavioral test sessions without adding much to testing time or distracting the technician from the principal task at hand. Overall wildness and placidity ratings obtained by combining capture and hold ratings provide a good impression of the difficulties encountered while working with lab mice in the course of complex experiments. Ratings of 21 inbred strains during the course of 15 behavioral tests in two laboratories demonstrated that the SPRET/Ei, PERA/Ei, CAST/Ei and SWR/J strains were particularly difficult to handle. The NOD/LtJ strain posed no special challenge in the Edmonton laboratory but was very difficult to handle in the Portland lab. The rating scales should be useful for judging the difficulties in working with novel targeted or induced mutations in mice as well as effects of a variety of environmental treatments or drugs.
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.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".