Best practice recommendations for the use of fully implanted telemetry devices in pinnipeds
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Electronic telemetry devices have enabled many novel and important data collection and experimental opportunities for difficult to observe species. Externally attached devices have limited retention and may affect thermoregulation, energetics, social and reproductive behavior, visibility, predation risk and entanglement. Internally placed, surgically implanted devices can mitigate some of these effects and may open additional experimental opportunities. However, improper implementation can significantly affect animals and data. From a review of recent studies using fully implanted tags and studying their effects, we present 15 specific best practice recommendations for the use of such tags in pinnipeds. Recommendations address issues including device size, coating and sterilization, implantation surgery and effect assessment, within the framework of the Three R’s: Reduction, Refinement, Replacement. While developed for pinnipeds, these recommendations could apply to other aquatic mammals and vertebrates and to partially implanted or even external tags.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it