Aplicação de microtomografia computadorizada em estudos geológicos: a visualização 3D de estruturas rúpteis
Bibliographic record
Abstract
This paper describes the methodology applied in five basalts samples from Serra Geral Formation, Santa Catarina State, Brazil, using images obtained by X-ray computed tomography (μCT), which allow 3D visualization. The rocks samples were oriented collected and sent to the Soil Imaging Laboratory - Guelph University, in Canada, for the images acquisition and processing. The steps for the enhancement of micro-brittle structures and mineral density differences, termed in this study as anisotropic markers, consist of filters to detect edges, smoothing filters and particle analysis. The results are shown in rose diagrams for each axis (X, Y and Z) of the samples and was established the relationship between the axis and the surface fault system. In order to evaluate whether the methodology can be applied to oriented rock without the fault surface, another set of images were analyzed, based on a subvolume of the samples, without the surface fault. The results showed that the new technology can be applied in oriented rock sample, even if the main fault system was not identified in the field, and the axis with the more homogeneous direction define the direction of the main fault system. Special attention has to be given to the presence of ring artifact that influences the results of the analysis.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".