Near disappearance of the Angelshark <i>Squatina squatina</i> over half a century of observations
Bibliographic record
Abstract
Abstract Marine extinctions are particularly difficult to detect and almost all have been discovered after the fact. Retrospective analyses are essential to avoid concluding no‐extinction when one has occurred. We reconstruct the Angelshark population trajectory in a former hotspot (Wales), using interviews and opportunistic records. After correcting for observation effort and recall bias, we estimate a 70% (1.5%/year) decline in abundance over 46 years. While formerly widespread, Angelshark distribution contracted to a central core of Cardigan Bay. Angelshark declined almost unnoticed in one of the best‐monitored and most intensively managed seas in the world. Bycatch may be minimized by limiting netting on shingle reefs in Cardigan Bay. We provide the first quantitative time series to reveal the timing and trajectory of decline of Angelshark in the coastal waters of Wales and uncover historical centers of abundance and remnant populations that provide the first opportunity for the focus of conservation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".