Canada Lynx (<em>Lynx canadensis</em>) detection and behaviour using remote cameras during the breeding season
Bibliographic record
Abstract
The efficacy of surveys in detecting Canada Lynx (Lynx canadensis) can vary considerably by geographic area. We conducted surveys using digital passive infrared trail video-cameras from January to April 2013, during the breeding season of the Canada Lynx, in the John Prince Research Forest in central British Columbia. We used snow-track surveys to test the efficacy of our camera surveys. We measured trail camera detection rates by survey week and location and we noted Canada Lynx activity and behaviours recorded by the cameras. The detection rate increased between January and April, reaching a peak of 8 Canada Lynx/100 camera-days in early April. Canada Lynx spent more time at camera sites displaying behaviours such as scent-marking and cheek-rubbing in late March. The combination of both snow-track and trail camera surveys was especially effective, with Canada Lynx detected at 77% of all monitored sites. Depending on survey objectives, it may be beneficial to conduct camera as well as other non-invasive survey methods for Canada Lynx during the breeding season, when survey efficacy and detection rates are maximized.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".