Filling gaps: fishing, genetics, and conservation of groupers, especially the comb grouper (badejo) ( <i>Mycteroperca acutirostris</i> ), in SE Brazil (2013-2020)
Bibliographic record
Abstract
Abstract There are large gaps in our knowledge of the biology of important fish consumed by people in tropical countries, which makes conservation difficult. Small-scale fisheries are difficult to study and regulate, especially in countries with no systematic species monitoring. It is even more difficult to estimate the influence of these fisheries on vulnerable fish species and to diagnose possible damage to local fish populations. In this study, 490 individuals of badejo , or comb grouper ( Mycteropeca acutirostris) , were observed at the Posto 6 fishery in Copacabana, Rio de Janeiro, for the periods of 2013-2014 and 2018-2020. A pattern of decreasing catches was observed for comb grouper. Therefore, provided that the fishing gear and the number of fish have remained the same, the apparent decrease in comb grouper needs to be further investigated. The results provide information regarding the reproduction of comb grouper, with major spawning season around spring (September-December) and additional spawning during April in SE Brazil. Samples from 96 groupers along the coast of Brazil were obtained, and genetic analyses were conducted. The genetic information obtained for grouper species enabled us to determine the relative genetic proximity of M. acutirostris and Mycteroperca bonaci and to obtain information that can be useful for aquaculture and conservation.
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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 | 0.000 |
| 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".