Bibliographic record
Abstract
Fracture toughness is an important parameter to study fracture characteristic of rock under external loads. Based on splitting tensile test on flattened Brazilian disc specimen of rock after high temperature, load–displacement curves of rock sample in the fracture process are obtained and three mechanical parameters of rock including fracture toughness, splitting tensile strength and elastic modulus are calculated according to the experiment. Then, the change rules of fracture toughness, splitting tensile strength and elastic modulus with temperature are discussed, and the relations between splitting tensile strength, elastic modulus and fracture toughness are established. Experimental results show that there exist two inflection points in load–displacement curves. The fracture toughness, splitting tensile strength and elastic modulus reduce gradually with increasing temperature, among which, the mechanical parameters of granite decrease approximately linearly while that of marble decrease approximately as exponential function. There is a close connection between splitting tensile strength, elastic modulus and fracture toughness, nearly a good linear relationship. Since the test method of splitting tensile strength is relatively simple and that of fracture toughness is complex, the fracture toughness can be roughly estimated by splitting tensile strength.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.977 | 0.974 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".