Índice canadiense de calidad de las aguas para la cuenca del río Naranjo, provincia Las Tunas, Cuba
Bibliographic record
Abstract
El uso de índices para valorar la calidad de las aguas facilita su comunicación y entendimiento por especialistas y público en general. Uno de los más empleados es el propuesto por Canadian Council of Ministers of theEnvironment, conocido como CCME_WQI (por sus siglas en inglés) por la flexibilidad en la selección de las variables considerar. En este trabajo se utilizó el CCME_WQI para evaluar la calidad de las aguas con fines de riego de fuentes superficiales y subterráneas de la cuenca del río Naranjo, provincia Las Tunas, Cuba. Se utilizaron criterios de FAO y del Instituto de Ingeniería Agrícola de Cuba para definir los valores deseables. Los resultados muestran que las aguas son clasificadas como Pobres para el riego de cultivos agrícolas.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 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".