A review of the effects of different marking and tagging techniques on marine mammals
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
Wildlife research often requires marking and tagging animals to collect data on survival, reproduction, movement, behaviour and physiology. Identification of individual marine mammals can be carried out using tags, brands, paint, dye, photogrammetry, telemetry and other techniques. An analysis of peer-reviewed articles published from January 1980 to April 2011 addressing the effects of marking revealed a preponderance of studies focussed on short-term effects such as injuries and behavioural changes. Some marking techniques were reported to cause pain and to change swimming and haul-out behaviour, maternal attendance, and duration of foraging trips. However, marking has typically not been found to affect survival. No published research has addressed other possible long-term effects of marking related to injuries or pain responses. Studies of the more immediate effects of marking (mostly related to externally attached devices such as radio-transmitters) have shown a variety of different types and magnitudes of responses. It is important to note that studies failing to find treament differences are less likely to be published, meaning that the present and any other reviews based on published literature may be a biased sample of all research conducted on the topic. Publishing results that found no or low impacts (i.e. best practices) as well as those that found significant impacts on animals should both be encouraged. Future research under more controlled conditions is required to document acute effects of marking, including injury and pain, and to better understand longer-term effects on health, reproduction and survival. We recommend that studies using marked animals standardise their reports, with added detail on methodology, monitoring and sampling design, and address practices used to minimise the impact of marking on marine mammals.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.000 | 0.001 |
| 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