Espessuras do Grupo Serra Geral em Santa Catarina como resultado de um processo de estruturação em blocos.
Bibliographic record
Abstract
As espessuras do Grupo Serra Geral, da Bacia Geológica do Paraná, despertam grande interesse por constituir a principal cobertura do Sistema Aquífero Guarani (SAG). Recentemente a tese de doutorado de Descovi Filho, 2015, produzida no âmbito do Projeto Rede Guarani/Serra Geral (Meta 1 Componente 1), apresentou detalhes de campo e agregou informações de diversas fontes sobre 132 poços que atingem o contato do Serra Geral com o SAG, e portanto, possibilitam obter-se informações referentes a espessuras do pacote vulcânico e a definição de (pelo menos) 14 blocos tectônicos hidrogeológicos no Estado de Santa Catarina, com a espessuras do Grupo Serra Geral variando desde zero (0) metro até 1132 metros. O entendimento e conhecimento das espessuras do Grupo Serra Geral pode subsidiar a gestão dos recursos hídricos do Sistema Aquífero Iintegrado Guarani/Serra Geral (SAIG/SG)em todo o oeste de Santa Catarina.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".