Bibliographic record
Abstract
O presente artigo analisa as publicacoes de estudos de casos nesta ultima decada, sobre a gestao integrada de recursos hidricos. Para tal, foi feita uma busca sistematica da literatura, nas bases de dados Scopus e SciELO. As publicacoes categorizadas foram divididas entre os paises objetos dos estudos de casos selecionados, quais sejam: Estados Unidos, Canada, Israel, Suecia, China, Holanda, Australia, Vietna, Tailândia, Escocia, Oma, Brasil e Colombia. Sao apresentados os objetivos de cada estudo de caso, alem dos problemas apontados em cada lugar e as respectivas solucoes apontadas e desafios. Dentre os problemas apontados se destaca o declinio no numero de especies e populacoes de peixes; poluicao das aguas; governanca ambiental desconectada; falta de agua, devido ao aumento do consumo, combinado com a diminuicao das chuvas. Quanto as conquistas, uma inovacao e a “conta de agua ambiental”, especificamente na California. O Canada alterou a legislacao ambiental. Israel estabeleceu uma nova autoridade de agua e a China obteve importantes resultados na recuperacao da bacia hidrografica do rio Yangtze.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".