Seychelles tuna bulletin : fourth quarter 1989
Bibliographic record
Abstract
The number of purse seiners active in the Western Indian Ocean increased to 51 during the last quarter of 1989, to peak at 52 vessels in November, this being the highest number of vessels recorded in this fishery so far. During the same period last year the number of vessels in operation increased from 43 in October to 48 at the end of the year. The overall fishing performance of the fleet throughout the year is comparable to that obtained in previous years. The fishing results however were not as good as that obtained during 1988. Daily catch rates averaged 18.6 MT, compared to 22 MT in 1988 and 17.9 MT in 1987. Skipjack was the predominant species caught, comprising 67% of the catch with a corresponding marked decrease in the proportion of yellow fin from 47% in 1988 to 31% in 1989. The fishing pattern was somewhat different to that observed in previous years: as yellow fin catch rates were unusually low and remained depressed throughout the year. The fishing effort was more widely distributed as vessels searched for yellow fin, or congregated in locations where excellent skipjack catches prevailed. The skipjack fishing season starting April/May around the Mozambique Channel was cut short as was also the case in the previous two years. The change in yellow fin availability is believed to be caused by unfavorable oceanographic conditions rather than due to stock depletion, whereby the fish remained deeper and thus less accessible to the fishing vessels. As determined from seiner logbooks received by the 31st of December 1989 the cumulative catch by purse seiners in the Western Indian Ocean now stands at 221,017 tones for 1989. It is estimated that the total landings would reach 230,000 MT, the same level as that recorded in 1988. \nDuring 1989, new arrangements were reached with Japanese Fishing Companies and other private companies, allowing additional purse seiners to fish in the Seychelles EEZ. The EEC Agreement was in the process of being re-negotiated.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.099 | 0.054 |
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".