Classifying southern stingray activity states across abiotic factors in Belize coral reef ecosystems
Bibliographic record
Abstract
Elasmobranchs often exhibit nocturnal or crepuscular activity, with shark diel patterns being better understood than ray diel patterns. We used accelerometry and hidden Markov models (HMMs) to classify female southern stingray ( Hypanus americanus Hildebrand & Schroeder, 1928) activity states across diel periods and environmental conditions in Belize. Three state (low, medium, and high activity) HMMs were constructed for all individuals together and separately ( N = 9). Combined, stingrays were most likely to be highly active at night and in low and medium activity states in the morning. However, there was individual variation in diel activity. In contrast, all stingrays consistently used shallow water (<4 m) during periods of high activity. Temperature had less influence on activity patterns, although three individuals exhibited high activity in cooler water. Generally, high stingray activity was driven by diel cycles and depth. Future research should link activity states to specific behaviours, include a larger sample size, extend tag deployment durations, and explore the impact of predator and prey dynamics on stingray activity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".