Post-tagging behaviour and habitat use in shortnose sturgeon measured with high-frequency accelerometer and PSATs
Bibliographic record
Abstract
External tagging of fish using pop-up satellite tags (PSATs) can cause trauma and stress associated with capture, handling, tagging injury and tag placement that impedes body function and mobility, and these can affect the behaviour of the fish. We measured short-term (days) post-release behavioural response of estuarine shortnose sturgeon to tagging with PSATs and high-frequency accelerometers. We developed a secure, low-noise attachment method for high-resolution (50 Hz) accelerometer PSATs in shortnose sturgeon. The archived time series of acceleration was used to determine sturgeon post-tagging activity, estimate swimming speed, erratic behaviour and behavioural clusters in relation to ambient light level and temperature, depth and tidal flow. Short-term (hours) post-release response was characterized by resting periods on the river bottom and decreased swimming activity that was associated with individual-specific modulations in the swimming gait and high-energy burst acceleration movements. Locomotion routines suggested a relation to tidal flow, yet the short-term time series did not allow for routine movements to be classified. The approach used provides a useful method of revealing behavioural modifications during the post-release recovery period of PSAT-tagged fish. We discuss how short-term (acute) effects on behaviour and potential longer-term (chronic) effects on survival are especially relevant in tagging studies.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".