AVALIAÇÃO DA ACURÁCIA DOS ORTOMOSAICOS E MODELOS DIGITAIS DO TERRENO GERADOS PELO ΜVANT/DNPM
Bibliographic record
Abstract
This present paper aims to demonstrate the evaluation of the accuracy of orthomosaics and Digital Terrain Models(DTM) generated by the Unmanned Aerial Vehicle (UAV) developed by the University of Brasilia (UnB) in partnershipwith the National Department of Mineral Production (DNPM). This study evaluated the orthomosaic and the MDTfrom a pile of laminated limestone exploitation tailings in the Santana do Cariri municipality, state of Ceará, processedin three diff erent situations: (1) without the use of ground control points; (2) using 4 ground control points, located inbuildings around the stack; and (3) using10 ground control points, pre-signaled on the surface of the tailing pile. The assessment of accuracy was performed from the trend analysis and accuracy of the models, and the results classifi edaccording to the Standard Cartographic Accuracy of Digital Cartographic Products (PEC-PCD). The results showedthat the evaluated products are precision and reliability compatible with those obtained by conventional aerial photogrammetry, if properly oriented by ground control points.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".