USO DE INSTRUMENTO DE SUPORTE À TOMADA DE DECISÃO PARA GESTÃO DOS RECURSOS HÍDRICOS NO ESTADO DE MINAS GERAIS
Bibliographic record
Abstract
The aim of this study was to evaluate the application of the National Water Resources Policy (PNRH) in Minas Gerais state, analysing the implementation of its instruments. In order to achieve this, two indicators related to the implementation of the PNRH instruments (composed of five verifiers) and the performance of the river basin committees (composed of three verifiers) in each Planning and Management Unit for Water Resources (UPGRH) were established. Each verifier was analysed in relation to its compliance percentage. Weights were also assigned to verifiers through the Analytical Hierarchical Process. Based on these figures, it was possible to calculate the Effective Contribution Index of the PNRH instruments in the state of Minas Gerais, estimated at around 71%. Although the index is considered high, the approval of water bodies classification, charging for water use, and operation of river basin agencies is still insufficient in the state. The methodology applied in the present study proved to be adequate for the evaluation of the proposed criteria, allowing, also, the aggregation of new criteria for the evaluation of PNRH management instruments.
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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 | 0.018 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".