Comparing handline and trolling fishing methods in the recreational pelagic fishery in the Gulf of Oman
Bibliographic record
Abstract
The choice of fishing gear and catching strategy should be taken into consideration in the management of fish stocks. Here, paired fishing trials in a pelagic recreational fishery compared the catch composition, catch rate and size selectivity between handline and trolling fishing methods in Iranian coastal waters of the Gulf of Oman. Total catch rate was 1.06 fish hr–1 vs 0.88 fish hr–1 for handline and trolling, respectively, a 17% difference which was significant (p < 0.05). Generally, the handline method captured more fish than trolling for most species, but size selectivity tended to be species-specific per gear type. The handline fishing method captured larger talang queenfish (Scomberoides commersonnianus), while trolling captured larger narrow-barred Spanish mackerel (Scomberomorus commerson), pickhandle barracuda (Sphyraena jello) and Indian threadfish (Alectis indicus). Technical measures, such as gear restrictions, could be applied to recreational pelagic fisheries management in the Gulf of Oman. Such measures could improve species-specific exploitation patterns.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".