A Direct Comparison of Enclosed Track Plates and Remote Cameras in Detecting Fishers, <em>Martes pennanti</em>, in North Dakota
Bibliographic record
Abstract
Fishers (Martes pennanti) historically were reported to occupy forested areas of northeastern North Dakota, but the population was presumed extirpated during the 1900s as a result of overtrapping. Recently (≤15 years), Fishers have been recolonizing the state, and there is increasing interest in developing approaches for monitoring the population. During the period June–August 2008, we compared the efficacy of remote cameras and enclosed track plates in detecting Fishers in riparian forest along portions of the drainage basin of the Red River of the North in eastern North Dakota. We monitored 122 scent stations, each composed of both detection devices, with the remote camera positioned to monitor the entrance of the enclosed track plate. Fishers were detected at 40 of the 122 scent stations (32.8%) distributed along approximately 790 km of riparian forest. Among those 40 stations, Fishers were detected by both camera and track plate at 28 stations (70.0%), by camera only at 9 stations (22.5%), and on track plates only at 3 stations (7.5%). Overall, Fishers were detected 37 times by camera (92.5%) and 31 times on a track plate (77.5%). From photographic evidence at the 37 stations where Fishers were detected by camera, we determined that the average latency to initial detection was 4.8 days (SE 0.3, range 1–8). Among the 37 stations where Fishers were detected by camera, detections most frequently occurred on one (27 sites) (73.0%) or two days (7 sites) (19.0%) of a detection period.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".