Hierarchical approach to the assessment of fishing effects on non-target chondrichthyans: case study of <i>Squalus megalops</i> in southeastern Australia
Bibliographic record
Abstract
A three-levelled hierarchical risk assessment approach was trialed using piked spurdog (Squalus megalops) to evaluate the suitability of the approach for chondrichthyan species. At level 1, a qualitative assessment indicated that the only fishing-related activity to have moderate or high impact on S. megalops was "capture fishing" by otter trawl, Danish seine, gillnet, and automatic longline methods. At level 2, a semi-quantitative assessment ranked S. megalops at risk because of its low biological productivity and, possibly, its catch susceptibility from cumulative effects across the separate fishing methods. Finally, at level 3, a quantitative assessment showed that population growth is slow even under the assumption of density-dependent compensation where the fishing mortality rate equals the natural mortality rate. Although published information indicates that relative abundance has been stable in several regions of southern Australia, it is concluded that given its low biological productivity, changed fishing practices leading to increased fishing mortality could quickly put S. megalops at high risk. The hierarchical approach appears particularly useful for assessment of chondrichthyan species in data-limited fisheries. This approach allows for a management response at any level, optimizing research and management efforts by identifying and excluding low-risk species from data intensive assessments.
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How this classification was reachedexpand
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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".