Integração e análise de dados aerogamaespectrométricos, aeromagnetométricos e SRTM como ferramenta de suporte no mapeamento geológico em área do Terreno Granito-Greenstone de Rio Maria, região de Xinguara
Bibliographic record
Abstract
This paper aims to present the results obtained by the integration and analysis of geophysical data and Digital Elevation Model (DEM) images as an important tool in geological mapping in an area located in the Rio Maria Granite-Greenstone Terrane (RMGGT), in the Central Amazonian Province (Tassinari & Macambira, 2004) or Carajás Province (Santos, 2003), southeastern Amazonian Craton, Xinguara area, southeastern Pará.The aerogammaspectrometric and aeromagnetometric data used for this study were acquired by the Brazil-Canada Geophysical Project (PGBC) and the digital elevation images by the Shuttle Radar Topographic Mission (SRTM).The integration and analysis of these data showed to be very useful for geological mapping, specially to distinguish the different lithologies and help to select key areas for more detailed verification during the field mapping.At the end of this study, it was elaborated a geological map for the selected area.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".