Temperature observations in Antarctic tafoni: implications for weathering, biological colonization, and tafoni formation
Bibliographic record
Abstract
Tafoni have long been recognized, measured and discussed within the Antarctic context. However, with respect to the formative processes tafoni still remain somewhat of an enigma. In terms of the weathering attributes of tafoni, one problem is the monitoring of environmental conditions without the transducers themselves altering that environment. The application of ultra-small thermocouples provides an avenue for monitoring of rock surface temperatures without influence on the tafoni environment. At an Antarctic site temperatures were measured both inside and outside of a tafone, with data at 20 second intervals. These data show a spatial variability that may help explain tafoni development, at least in terms of weathering. Humidity data indicate that moisture conditions are very low such that water-based weathering processes are temporally and spatially constrained. The presence of several episodes of extreme temperature variations indicates that thermal stress may be an important contributor to weathering here. It is argued that the absence of any endolithic communities (at this site) within the sandstone, in which the tafoni develop, is a reflection of weathering rates that exceed the ability of organisms to invade and colonize the rock. At the present time, weathering appears to be primarily in the form of granular disintegration and flaking.
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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 | 0.001 |
| 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".