Rock thermal data at the grain scale: applicability to granular disintegration in cold environments
Bibliographic record
Abstract
Abstract Consideration of the mechanisms associated with the granular disintegration of rock has been limited by available data. In most instances, both the size of the transducer and the nature of the study have negated any applicability of the resulting data to the understanding of grain‐to‐grain separation within rock. The application of microthermocouples (≤0·15 mm diameter) and high‐frequency logging (20 s intervals) at a taffoni site on southern Alexander Island and from a rock outcrop on Adelaide Island (Antarctica) provide new data pertaining to the thermal conditions, at the grain scale, of the rock surface. The results show that thermal changes (ΔT/t) can be very high, with values of 22 °C min−1 being recorded. Although available data indicate that there can be differences in frequency and magnitude of fluctuations as a function of aspect, all aspects experienced some large magnitude (≥2 °C min−1) fluctuations. Further, in many instances, large thermal changes in more than one direction could occur within 1 min or in subsequent minutes. These data suggest that the surface grains experience rapidly changing stress fields that may, with time, effect fatigue at the grain boundaries; albedo differences between grains and the resulting thermal variations are thought to exacerbate this. The available data failed to show any indication of water freezing (an exotherm) and thus it is suggested that microgelivation may not play as large a role in granular breakdown as is often postulated for cold regions, and that in this dry, Antarctic region thermal stress may play a significant role. Copyright © 2003 John Wiley & Sons, Ltd.
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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 | 0.001 | 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".