Segregated ice structures in various heaved permafrost landforms through CT Scan
Bibliographic record
Abstract
Abstract The growth of segregated ice lenses in frost susceptible sediments in the discontinuous permafrost zone is the dominant mechanism for the formation of permafrost mounds, such as palsas, lithalsas and permafrost plateaus. Thawing of these mounds creates thermokarst lakes, which are particularly abundant in Nunavik, east of the Hudson Bay area. The inception of the permafrost in mounds and their growth are regulated by climate conditions, by local Quaternary geology and by environmental factors such as topography, vegetation, snow cover and surface humidity. Variable sizes and morphology of the permafrost mounds can be attributed to local factors that affect the ice segregation process, particularly the supply of water needed for ice‐lens growth and grain‐size composition of the soil into which aggradation takes place. Computer image analysis of CT scans on high quality cores obtained from permafrost mounds and plateaus of various shapes reveal that the ice layer sequences and permafrost internal structure vary with landform types. A relationship therefore exists between different morphological type within a family of landforms and their microscale internal structure. Copyright © 2007 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 | 0.001 |
| 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) | 0.002 | 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".