Designing and evaluating length-frequency surveys for trap fisheries with application to the southern rock lobster
Bibliographic record
Abstract
A survey design for estimating the length distribution of harvested southern rock lobsters (Jasus edwardsii) was developed for the South Australian fishery. Experimental sampling was carried out by volunteer fishers in spring 1996 and autumn 1997 to test three proposed survey designs. A variance components analysis indicated that it would be more efficient to sample one pot per trip from all trips rather than the previous design of sampling multiple pots from a few trips. The variation among licenses (fishers) accounts for most of the remaining sample variance. Onboard research sampling by scientists, who in the past measured from all pots on selected trips, was shown to be the least efficient design option in comparison with volunteer sampling by fishers. A sampling protocol where fishers measure one to three pots per trip has been adopted by the South Australian rock lobster fishers. Estimators, based on a three-level sampling hierarchy of pot, day, and license, are presented for estimating the mean and sample variance of the numbers harvested overall and within each length category.
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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 | 0.032 | 0.083 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".