Evaluation of satellite collar sample size requirements for mitigation of low-level military jet disturbance of the George River caribou herd
Bibliographic record
Abstract
Wildlife radio-telemetry and tracking projects often determine a priori required sample sizes by statistical means or default to the maximum number that can be maintained within a limited budget. After initiation of such projects, little attention is focussed on effective sample size requirements, resulting in lack of statistical power. The Department of National Defence operates a base in Labrador, Canada for low level jet fighter training activities, and maintain a sample of satellite collars on the George River caribou (Rangifer tarandus caribou) herd of the region for spatial avoidance mitiga¬tion purposes. We analysed existing location data, in conjunction with knowledge of life history, to develop estimates of satellite collar sample sizes required to ensure adequate mitigation of GRCH. We chose three levels of probability in each of six annual caribou seasons. Estimated number of collars required ranged from 15 to 52, 23 to 68, and 36 to 184 for 50%, 75%, and 90% probability levels, respectively, depending on season. Estimates can be used to make more informed decisions about mitigation of GRCH, and, generally, our approach provides a means to adaptively assess radio collar sam¬ple sizes for ongoing studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".