Ultrasonic vocalization analysis as a novel metric to assess home cage welfare in rats
Bibliographic record
Abstract
Laboratory rodent housing conditions vary significantly across laboratories and facilities. Variation in housing is implicated in animal stress leading to study variability and subsequently the ability to replicate experimental findings. Optimization and standardization of animal housing conditions are necessary to improve animal welfare and data consistency, thereby reducing the number of animals necessary to detect treatment effects. While interest in environmental enrichment is increasing, many studies do not examine the behavior of animals within the home cage, neglecting important aspects of enrichment. To determine the impact of increased vertical home cage area on animal welfare, double-decker cages (enriched), which allow animals to rear (stand on hind legs), were compared to single-level cages (standard), which impede the ability to rear. Home cage welfare was assessed by analyzing ultrasonic vocalizations, fecal corticosterone, rearing and agonistic behavior. Ultrasonic vocalization content was further explored by analyses of call type as defined by a 14 call-type schematic. Contrary to our expectations, rats housed in enriched cages spent more time fighting, produced less 50 kHz calls and had higher levels of fecal corticosterone. Standard caged animals attempted to rear more, but reared for a shorter amount of time due to the height limitation imposed by standard cages. Standard cages restrict some naturalistic behaviors such as rearing, but reduce agonistic behavior which may be attributable to their single-tier organization. Increased home cage height is beneficial, as it permits rats to engage in normal ethological behavior. However, the inclusion of a continuous "upper deck" appears to increase dominance/aggressivebehavior among cage mates.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".