A portable structure for identifying wolverines and Canada lynx using integrated cameras and hair snags
Bibliographic record
Abstract
Abstract Wolverine (Gulo gulo) and Canada lynx (Lynx canadensis), listed as threatened under the United States Endangered Species Act, inhabit remote mountainous terrain across multiple western states. To address challenges associated with collecting long‐term occupancy and demographic data for both species, we developed and tested a modified non‐invasive camera and hair snag (C&H) monitoring system for simultaneous long‐term monitoring of wolverine and Canada lynx (lynx hereafter). We aimed to adapt wolverine monitoring for concurrent use with lynx; redesign the data collection framework and station configuration for portability, affordability, and enhanced data capture; and establish the presence of individual wolverine and lynx through integrated photographic identification and genetic sampling. We validated the system over 5 field seasons by linking photographs to genotypes of individuals and identified reproductive status and sex of individuals across 23 stations spread over a non‐contiguous grid covering 1,425 km2 in western Montana, USA. We obtained individual genotypes for 13 (9 male, 4 female) of 19 wolverines (12 male, 7 female) and 6 (4 male, 2 female) of 12 lynxes (6 male, 4 female, 2 unknown) identified from unique markings in photographs. We also obtained photographic detections of bobcats (Lynx rufus), red foxes (Vulpes vulpes), and martens (American [Martes americana], Pacific [M. caurina]). The C&H stations offer an efficient, cost‐effective, and non‐invasive approach for mesocarnivore monitoring in remote mountainous regions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".