Lobster Fishery and aquaculture development in the North coast of Gulf of Oman: with emphasis on spiny lobster Panulirus homarus
Bibliographic record
Abstract
Spiny lobsters are one of the most important commercial and highly priced crustaceans along the Southern coast of Iran (Sistan and Baluchistan Province). In the last three decades, the economy of a large part of the fishermen population has been directly dependent on it. The lobster fishing rate decreased from 42 t in 1989 to 1 t in 2004. This has been attributed to the effects of improper fishing methods and overfishing. Meanwhile, Oman, as a leading country in the fishing industry in the Gulf of Oman, produced 450 t of lobster in 2016, compared to 416 t in 2015. Little attention has been paid to lobsters by related organizations. This neglect in framing and enforcing fishing regulations has led to heavy fishing pressure on this vulnerable resource along the southern coast of Iran. For this reason, some efforts have been made by researchers at the Iranian fisheries science research institute, such as the Preliminary study of lobster biology, feeding biology and ecology, designing the appropriate lobster trap, designing an artificial reef as a shelter for lobster; and some experimental research is currently underway to assess population dynamics and maximum sustainable yield (MSY). Furthermore, the release of artificially raised lobster juveniles contributes to the re-establishment or enhancement of lobster stocks. However, one of the main problems for successful restock programs has been the lack of inexpensive methods for juvenile production.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".