Factibilidad economico ambiental para el cultivo sostenible de ostion de mangle Crassostrea rhizophorae (Guilding, 1828), en Cuba
Bibliographic record
Abstract
We analyzed two variants in producing mangrove oyster Crassostrea rhizophorae in Cuba: 1) traditional fishery (EP) at natural beds partially supported by aggregating suspended collectors in the mangrove, and 2) artisanal farming (CA) totally supported by spat from the wild, settled in artificial collectors and "mother shell" strings, farming and harvesting on the same artifact and oyster boxes. We determined the economic and environmental feasibility of both variants projected to a five year period from cost-benefit analysis based on production data. Tax on total income established in Cuba was included, as well as estimated costs for environmental damage. Traditional fishery (EP) presents negative net profit in a five years period (with return value US$-1388.39 at fifth year), as well as being environmentally costly by the negative impact on the mangrove ecosystem. Artisanal farming (CA) provides positive return from the third year and positive net profit (US$731.78 at fifth year), reducing environmental damage to mangrove ecosystem and allowing a substantial increase in oyster production. We recommend actions to achieve aquaculture and sustainable management of the native oyster C. rhizophorae in Cuba.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".