Bibliographic record
Abstract
Abstract This paper reviews isotopic research on the characterisation and identification of various types of ground ice throughout the Canadian Arctic, including buried glacier ice, massive segregated ice, segregated ice lenses and offshore ice‐rich permafrost, as well as ice related to other cold‐region phenomena such as ice wedges, icings (aufeis), frost blisters and pingos. The formational age of ground ice bodies ranges from recent (seasonal ice in the active layer) to tens of thousands of years, when the region experienced widespread continental‐scale glaciation. Modern ice lenses generally have 18O/16O ratios of ‐18 to ‐22‰, while modern ice wedges usually range from ‐22 to ‐25‰. δ18O values as high as ‐14‰ are representative of the Hypsithermal period (4000 to 8000 years BP), while glacial‐age ice has been measured with 18O/16O ratios as low as ‐36‰. Buried glacier ice often preserves climatic variations from the time of snow deposition. Other massive ground ice bodies contain isotopic signatures (18O and 2H) that indicate variable fractionation of the isotopes during freezing of the source water at stationary freezing fronts in either open or closed systems. Placing the ice bodies into a time frame can be accomplished either through age dating of the enclosing sediments and encased organics, or by direct dating of the ice utilising tritium (3H) for relatively young ice and radiocarbon (14C) analysis of contained gas bubbles for older ice. Copyright © 2011 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 | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".