Influence des conditions climatiques sur le comportement du Lièvre d'Amérique (<i>Lepus americanus</i>) en semi-liberté
Bibliographic record
Abstract
Snowshoe hare (Lepus americanus) behavior has been analyzed over a1-year period to understand the influence of climatic factors. Six animals were observed with a video camera in a 1350-m2 outdoor enclosure located in a wood stand andequipped with a computerized weather station. Temperature (°C), relative humidity (%), windspeed (km/h), and barometric pressure (hPa) were recorded every 5 min during the entire study period. Every month, 72 h of observation were recorded to correlate those factors with feeding, locomotion, grooming, and resting behavior. Results indicate a marked influence of climatic conditions on hare behavior patterns. All patterns are more frequent when relative humidity is high or increasing. Locomotion and feeding are more common when temperature is low or decreasing, or when barometric pressure is increasing. Wind speed has a negative effect on the frequency of all behavioral patterns. Those effects are discussed in relation to hare biology. It appears that energetic constraints associated with harsh weather conditions have forced the snowshoe hare to adopt a flexible behavioral strategy.
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 | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".