Bibliographic record
Abstract
Abstract The maximum sustainable yield (MSY) of legal-size spiny lobsters Panulirus argus (Latreille) was estimated at 37 (±SE 7.7) × 10 3 animals by regression of catch per unit effort (CPUE) on total effort. A graphical plot of P. argus fishery catch and effort data for lobster seasons from 1975/76 to 1986/87 resulted in a second estimate of the P. argus MSY of 30 × 10 3 lobsters per season by a quadratic regression of catch on total effort. A graphical plot of catch on total fishing effort data for the Guinea chick Lobster Panulirus guttatus (Latreille), with a quadratic curve fit ( R 2 = 0.612), resulted in an estimate of MSY of approximately 33 × 10 3 lobsters per calendar year. The 1985 and 1986 fishery catches of Guinea chick lobsters were close to the MSY. There was an overall increase in the CPUE of P. argus lobsters (1975/76–1986/87), whereas there was an overall decline in the CPUE of P. guttatus spiny lobsters over the same time period. The two species interannual patterns of change of CPUE followed that of sea temperature change on the Bermuda Platform; superimposed was a 5-year cycle of CPUE, which was particularly noticeable with P. guttatus lobsters, suggesting a causal relationship with a 5-year cycle in the annual mean temperature of sea surface waters, averaged from six temperature stations on the Platform. Annual yield of P. argus lobsters was correlated with Platform average sea temperature at the 10% level (Spearman rank test). Both P. guttatus and P. argus yields on Platform sea temperature were parabolic in form. Platform CPUE of Guinea chicks on Hamilton Harbour temperature also suggested a parabolic relationship in the range 22–26 °C (coefficient of determination R 2 = 0.43). There was clearly a parabolic association between P. argus CPUE and Hamilton Harbour temperature over the same temperature range ( R 2 = 0.93). It is suggested that the Lellis and Russell quadratic model for survival and growth of P. argus postlarvae may be extended to juvenile P. argus to explain these findings.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.988 | 0.991 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".