Statistical behaviour of the deformation for first loading of polycrystalline ice
Bibliographic record
Abstract
Abstract A statistical analysis of the lengths of grain-boundary and transgranular cracks induced during the initial straining of columnar-grain ice by a compressive load applied perpendicular to the long direction of the columns is presented. The analysis shows that the crack lengths are randomly distributed and form distinct but correlated populations.The lognormal distribution function is shown to be a good descriptor of the populations for 5–90% of their range. Statistical models are presented for the lognormal behaviour of the crack-length distribution and for the strain dependence of the crack density. The models assume that a change in the value of the random variable of the respective population depends on the population value of the variable at the time of the change. It is shown that the model for the strain dependence of the crack density is suitable for the strain dependence of the acoustic emission, measured in both columnar-grain and granular ice subject to constant compressive loads. Evidence is also presented for a lognormal dependence of the dislocation density on strain. The analysis demonstrates that the cracks that form during the initial straining of polycrystalline ice are independent, random events and that the resulting crack populations are precursors to failure by fracture.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".