Detalle de la subcuenca 63 en la región hidrográfica del río Paraná
Bibliographic record
Abstract
O estudo abrange a parte Oeste do estado de São Paulo e a parte Leste do estado do Mato Grosso do Sul e os seguintes municípios: Água Clara, Anaurilândia, Bandeirantes, Bataguassu, Brasilândia, Camapuã, Campo Grande, Cassilândia, Chapadão do Sul, Costa Rica, Presidente Epitácio, Presidente Prudente, Presidente Venceslau, Promissão, Quatá, Queiroz, Quintana, Rancharia, Regente Feijó, Ribeirão dos Índios, Inocência, Rinópolis, Rosana, Rubiácea, Sagres, Salmourão, Santa Mercedes, Santo Anastácio, Santo Expedito, Santópolis do Aguapeí, São João do Pau d`Alho, Jaraguari, Teodoro Sampaio, Tupã, Tupi Paulista, Valparaíso, Vera Cruz, Nova Alvorada do Sul, Nova Andradina, Ribas do Rio Pardo, Santa Rita do Pardo, Selvíria, Sidrolândia, Três Lagoas, Adamantina, Alfredo Marcondes, Alto Alegre, Alvaro Machado, Alvinlândia, Andradina, Anhumas, Araçatuba, Arco-Iris, Bastos, Bento de Abreu, Bilac, Bora, Braúna, Cafelândia, Caiabu, Caiaua, Castilho, Clementina, Coroados, Dracena, Echopora, Emilianópolis, Euclides da Cunha Paulista, Flora Rica, Florida Paulista, Gabriel Monteiro, Galia, Garça, Getulina, Guaiçara, Gauimbe, Guaraçaí, Guarantã, Herculândia, Iacri, Indiana, Inubia Paulista, Irapuru, Itaurã, João Ramalho, Julio Mesquita, Junqueirópolis, Lavínia, Lins, Lutécia, Maraba Paulista, Mariápolis, Marília, Martinópolis, Mirandópolis, Mirante do Paranapanema, Monte Castelo, Murutinga do Sul, Nova Guataporanga, Nova Independência, Ocauçu, Oriente, Oscar Bressane, Osvaldo Cruz, Ouro Verde, Pacaembu, Panorama, Paraguaçu Paulista, Parapuã, Pauliceia, Penápolis, Piacatu, Piquerobi, Pirajuí, Pirapozinho, Pompéia, Pracinha, Presidente Alves e Presidente Bernardes. E os seguintes rios: Rio Anhaduí, Rio Anhanduzinho, Rio do Peixe, Rio Feio, Rio Aguapei, Rio Pardo, Rio Santo Anastácio, Rio Sucuriú e Rio Verde.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 teacher head, 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".