Dusky sharks (<i>Carcharhinus obscurus</i>) undertake large-scale migrations between tropical and temperate ecosystems
Bibliographic record
Abstract
Understanding the large-scale migrations of marine predators can allow better representation of their population dynamics. The migration biology of dusky sharks (Carcharhinus obscurus), a cosmopolitan large marine predator with very low resilience to fishing, was quantified using a large-scale network of acoustic receivers deployed across Western Australia. Time-series plotting of individual shark detections and modified logistic modelling were used to determine the timing of acoustically tagged sharks’ seasonal migration, the proportion of the population migrating, and the size at which sharks start to migrate. Large (>200 cm fork length) dusky sharks migrated between areas closed (north) and open (south) to commercial shark fishing. There was limited evidence that smaller sharks occurred in the northern study area, whereas several larger individuals of both sexes undertook repeated north–south displacements, moving between disparate ecosystems within the Indian Ocean (21.7°S–35.4°S) and covering round-trip distances of 2000–3000 km per migratory event. For migrating individuals, the probability of occurring in the north was high in the austral winter–spring and low (males) to moderate (females) during the austral summer–autumn.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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".