MAPSAR simulation campaign: evaluation of the SIVAM/SIPAM SAR system for geologic mapping in Carajás Mineral Province
Bibliographic record
Abstract
The Carajás Mineral Province is located in the eastern portion of the Amazon craton, state of Pará and contains a significant number of mineral deposits, most of them exhibiting structural and lithological controls, such as sets of dilation faults. This paper presents the results of the interpretation of simulated MAPSAR (Multi-Application Purpose SAR) data, integrated with aerogeophysical data, over a portion of the Province. The integrated SAR-geophysical data were assessed as auxiliary tools for geological and structural mapping, using data fusion techniques for generating imagery for geological interpretation. SAR images were produced by the SIPAM R99-B system and the airborne geophysical data by the Brazil-Canada Geophysical Project. Prior to fusion, SAR and geophysical data were individually processed for enhancing geological information. The results allowed establishing the relationship between the features extracted from fused images and the main lithologic and geomorphologic domains known in the area. These results demonstrate the potential of these data and methods for the geological analysis of areas of high metallogenetic potential in the Amazon, in support to regional mineral exploration programs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".