Análise espaço-temporal da cobertura vegetal e uso da terra na Interbacia do Rio Paraguai Médio-MT, Brasil
Bibliographic record
Abstract
O objetivo deste estudo foi realizar uma análise espaço-temporal da cobertura vegetal e do uso da terra na Interbacia do Rio Paraguai Médio-MT, Brasil, pelo geoprocessamento de imagens Landsat TM, dos anos 1991, 2001 e 2011. As imagens foram georreferenciadas, classificadas e processadas no software Spring e as classes temáticas, quantificadas e editadas no software ArcGis. Foram mapeadas sete classes, sendo as mais expressivas a vegetação nativa, a pastagem e a cana-de-açúcar. Os resultados indicaram alterações em todas as classes durante os últimos 20 anos, com a diminuição de 22,89% da vegetação nativa, relacionada com o aumento de 58,42% da pastagem e 490,26% de monocultura de cana-de-açúcar. Foi verificado o conflito de uso da terra, principalmente em áreas de mata ciliar, fato que pode influenciar negativamente na conservação da interbacia e, consequentemente, do pantanal mato-grossense.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".