Investigation of ice‐wedge infilling processes using stable oxygen and hydrogen isotopes, crystallography and occluded gases (O<sub>2</sub>, N<sub>2</sub>, Ar)
Bibliographic record
Abstract
Abstract The source and mechanism of infill of ice wedges of various ages (modern to Pleistocene) were examined for sites in the western Arctic. Several techniques were employed, including stable O‐H isotope and crystallographic analyses of the ice, and gas composition (O2, N2 and Ar) analyses of air entrapped in the ice. The results indicate that climatic and site‐specific conditions may influence the source of infilling during ice‐wedge growth, so that wedge ice in wet and dry environments exhibits different characteristics. For example, Vault Creek tunnel (Alaska) ice wedges, dating from the Late Pleistocene, a cold and dry period, preserved stable O‐H isotopes and gas compositions similar to those expected for ice formed by snow densification. In contrast, ice wedges from the Old Crow region (Yukon), dating from the Late Holocene, preserved isotopic and gas compositions more comparable with those expected for ice formed by the freezing of liquid water. In both ice‐wedge types, the δ(O2/Ar) values are much lower than both dissolved and atmospheric values, which may be due to the respiration of microorganisms living within ice bubbles or interstitial water at the grain boundaries. The elevated δ18OO2 (up to 16‰) of the occluded gases supports the occurrence of microbial respiration. However, the δ(N2/Ar) values do not appear to have been affected by biological processes, and as such are reflective of the infilling processes. Copyright © 2010 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".