Economic Importance of Environmental Benefits and Costs for the North Coastal Zone in the Province of Camagüey, Cuba
Bibliographic record
Abstract
Environmental benefits and costs are very recurrent terms when they come to sustainable development. Keys for the north coastal area of Camaguey province, is a major tourist development plan in the medium term in Cuba. But is nonetheless a concern how to maintain environmental quality when important natural values are identified. It is a very fragile ecosystem that exists in the ten protected areas, of these one with international importance (Wildlife Refuge High River from Camaguey). Preliminary works’ hypothesis is that if you identify yourself to about the coat was five in the area Camaguey northern coastal ecosystem as increased interconnection planned tourism development in their keys, money are in your products and natural features and environmental costs are estimated to be able to evaluate the economic feasibility of environmental area through the benefit ratio cost. Correspondingly two objectives are identified: 1. Estimate the environmental benefits and costs in the northern coastal area of Camaguey and 2. Calculate the cost benefit relation methodological procedure designed and validated in the Territorial Project Analysis of the production of goods and services environmental in the north coastal area of the province of Camaguey, Cuba executed by CIMAC in 2010. The environmental and economic benefits for the ecosystem to date represent 39 pesos for every peso of environmental cost updated.
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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 | 0.001 | 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) | 0.003 | 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".