Contemporary stress state in the Zhao–Ping metallogenic belt, eastern China, and its correlation to regional geological tectonics
Bibliographic record
Abstract
Abstract In this article, the contemporary stress state of the Zhao–Ping metallogenic belt in eastern China was revealed using overcoring and hydraulic fracturing stress data, the relation between the stress field and geological tectonics was discussed, and the stability of regional faults under the present-day stress environment was evaluated. The results indicate that the stress level is considerably high, and the distribution of stress intensity is uneven. The stress regime is primarily characterized by σ H > σ v > σ h. The σ H orientation is well-oriented in the WNW–ESE, which is roughly identical to other stress indicators. Moreover, the σ H direction reflected by joint strikes and inferred based on the fault characteristics agrees fairly with the identified stress orientation. The modern stress field basically inherited the tectonic stress field of the Yanshanian and Himalayan periods but is principally dominated by the Himalayan period. Additionally, the calculated µ m ranges from 0.2 to 0.7, indicating that the possibility of shallow faults across this area being reactivated and experiencing shear failure is small overall under the current stress conditions. µ m = 0.2 and 0.5 are suggested as the lower and upper limits for predicting and analyzing future fault activity in the area, respectively.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| 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".