Short-term effects of camera trap installation on incubation constancy in cranes
Bibliographic record
Abstract
Research regarding how birds respond to the installation of cameras at nest sites is limited. We installed cameras at nests of Sandhill Cranes Antigone canadensis ( Linnaeus, 1758 ) and federally endangered Whooping Cranes Grus americana Linnaeus, 1758 in Juneau County, WI, as part of an ongoing study monitoring the reproductive success of Whooping Cranes in WI. The eastern population of Sandhill Cranes has grown, while Whooping Crane population growth has been slow, prompting the need to monitor the reproductive success of cranes on the refuge. We recorded the flight initiation distance during camera installation, the return time after camera installation, as well as measured the distance at which cameras were placed from each nest. We included temperature at camera deployment, age of nest, mode of access, ordinal date, and year in statistical regression models. We found an apparent difference in the observed flight initiation distances between the two species. Sandhill Cranes allowed researchers to approach their nests closer than Whooping Cranes prior to flushing. The post-disturbance return time was influenced by how far away the cameras were placed from the nest and the ambient temperature during camera deploy. Our study may help inform decisions regarding species response to methods and distance when deploying cameras, especially for endangered or disturbance-sensitive species.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".