Impact of lobster size on selectivity of traps for southern rock lobster (<i>Jasus edwardsii</i>)
Bibliographic record
Abstract
Most lobster fisheries are characterized by high exploitation rates. This has led to substantial declines in the size structures of the populations over time as larger lobsters have been removed. Although both scientists and fishers have suggested that size related hierarchies could impact on lobsters entering traps, the effect of the size change on the selectivity of lobster traps as a population's size structure changes has not been investigated. This paper demonstrates that larger lobsters affect the entrapment of smaller lobsters and that this behaviour affects the selectivity of lobster traps. Both spatial and temporal (within season) factors were found to affect the selectivity plots. Spatial differences in selectivity were attributed to the broader size range of larger lobsters found in regions of faster growth. Temporal differences were attributed to the decline in larger lobsters over the course of a season caused by exploitation. There are also differences in trap selectivity between the sexes.
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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) | 0.001 | 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 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".