Crack-seal patterns: records of uncorrelated stress release variations in crustal rocks
Bibliographic record
Abstract
Abstract Statistical properties of crack-seal veins are investigated with a view to assessing stress release fluctuations in crustal rocks. Crack-seal patterns correspond to sets of successive parallel fractures that are assumed to have propagated by a subcritical crack mechanism in the presence of a reactive fluid. They represent a time-sequence record of an aseismic and anelastic process of rock deformation. The statistical characteristics of several crack-seal patterns containing several hundreds of successive cracks have been studied. Samples were collected in three different areas, gold-bearing quartz veins from Abitibi in Canada, serpentine veins from the San Andreas system in California and calcite veins from the Apennine Mountains in Italy. Digitized pictures acquired from thin sections allow accurate measurement of crack-seal growth increments. All the samples show the same statistical behaviour regardless of their geological origin. The crack-seal statistical properties are described by an exponential distribution with a characteristic length scale and do not show any spatial correlation. They differ from other fracture patterns, such as earthquake data, which exhibit power-law correlations (Gutenberg-Richter relationship). Crack-seal series represent a natural fossil record of stress release variations (less than 50 bars) in the crust that show a characteristic length scale, associated with the resistance of rock to effective tension, and no correlation in time.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".