A review of Impacts of Tracking Devices on Birds
Bibliographic record
Abstract
Over the past few decades, extrinsic tracking devices (e.g., radio transmitters, GPS loggers, satellite transmitters, geolocators) have been widely used to study wildlife movement and other demographic parameters.Remote tracking and monitoring technology is continually advancing, and its use by researchers is becoming more widespread.Minimizing any potential impacts of tracking devices on focal species is of upmost importance in order to ensure and promote animal welfare and reliable scientific information.Many researchers aim to understand any potential short-or long-term impacts of remote tracking, and to develop methods that support the responsible and safe tagging of birds (e.g., Geen et al. 2019).As tracking projects become more mainstream, it is critical that banders and researchers stay up to date and contribute to current base of knowledge on the topic.This review summarizes available research demonstrating the impacts of attaching a variety of tracking devices to birds in order to guide and promote minimally invasive methods of deploying tracking devices, and to highlight the need for continued study of the effects of devices and attachment methods on bird welfare.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".