Trends in trawl and purse seine catch rates in the north-eastern Mediterranean
Bibliographic record
Abstract
Data on fishing effort expressed in vessel days at sea and corresponding landing/day for a large number of species have been collected by the Institute of Marine Biological Resources (IMBR) since the second half of 1995. Data were collected over a grid of 21 stations throughout the Greek seas. In the present study we analyzed the monthly days at sea as well as catch per day for trawlers and purse seiners from 1996 to 2000, by general linear models and trend analysis. The following vessel size groups per gear were considered: (a) trawlers smaller and larger than 20m; (b) purse-seiners smaller and larger than 15m. Collected data were also aggregated for five fishing sub-areas: the North Aegean, the Central Aegean, the South Aegean, Cretan waters and the Ionian Sea. Trend analysis of landing/day time series indicated that demersal and pelagic resources are declining in the main fishing grounds. Declining landing/day trends are regarded as indicators of overfishing, especially in the light of the fact that high catch rates are maintained by fishing in ‘hot spots’. The results of the present analysis provide, for the first time, important information on the sustainability of the fisheries in the north-eastern Mediterranean, an area characterized by a complete lack of accurate long-term data on effort and catch per effort
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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 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".