No evidence that cameras affect shorebird nest survival on the coastal plain of Arctic National Wildlife Refuge, AK
Bibliographic record
Abstract
Cameras are important tools used to determine nest fate, identify predators and evaluate behaviour; however, they may impact the parameters they are used to measure, thereby biasing results. We evaluated the impact of cameras ˜ 10 m from the nest on shorebird nest survival at the Canning River Delta, Alaska, 2017–2018 (ncontrol = 122, ncamera = 109) using a much larger sample size than in previous studies conducted in the Arctic and random assignments at nest discovery. We found no effect of camera presence at the nest on daily nest survival (model‐averaged daily survival rate (DSR) 85% confidence interval (CI); control: 0.971–0.983, camera: 0.969–0.982). We suggest that nest survival studies of tundra‐nesting birds should consider the use of cameras to minimize researcher disturbance, increase the accuracy of fate assignments, and broaden the ecological data collected (e.g. incubation behaviour, predator identification and non‐anthropogenic non‐predation disruption such as by caribou).
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".