A statistical model for presence of late-season frozen ground in discontinuous permafrost at Dublin Gulch, Yukon
Bibliographic record
Abstract
This paper describes geostatistical analyses completed at a discontinuous permafrost site in central Yukon to develop a predictive model for the presence of late-season frozen ground in support of planning and design for potential site development. The most important factors in the bivariate statistical model were soil type, as determined through terrain analysis, and slope aspect, as inferred from available topographic data. The other three factors included in the final model were profile curvature, slope angle, and ground elevation, each interpreted from available topographic data. The resulting model subdivides the site into three broad classes of frozen ground likelihood: low, where frozen ground can be expected to be encountered in late summer at 15% of observation locations; medium, where 50% of the ground is expected to remain frozen; and high, where 85% of the ground is expected to remain frozen. New test pit and borehole data from the summer of 2012 were used to verify model performance. The inferred correlations between frozen ground and soil type, aspect, curvature, slope, and elevation obtained in this case study may provide useful information relative to expected permafrost occurrence at sites in central Yukon with similar geology and physiography.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 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".