Modelling air, ground surface, and permafrost temperature variability across four dissimilar valleys, Yukon, Canada
Bibliographic record
Abstract
Spatial maps of the air and ground thermal regime were generated for four Yukon valleys. The aim was to model air, ground surface, and ground temperature (at fine spatial resolution) using locally measured inverted surface lapse rates (SLR) to better predict temperature along an elevation gradient. These local models were then compared to a regional permafrost probability model, which utilized differing inversion assumptions, as well as circumpolar and national models generated without considering inversions. Overall, permafrost probability in the regional model matched well with the local models where assumptions of treeline and inverted SLRs held true. When normal SLRs were assumed, permafrost presence was overestimated in each valley. This discrepancy was greatest at high elevations where permafrost was predicted to be the coldest and most widespread. However, the difference between valleys was dependent on surface and subsurface characteristics such as higher snow cover, mature forest, or thick organic layers which show a greater disassociation from the air temperature overall. Appropriate characterization of the SLR is essential for accurate predictions of the ground thermal regime’s spatial distribution and permafrost presence. These models also provide a starting point for better predictions of warming in these valleys and other areas subject to inversions of similar magnitudes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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 teacher head, 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".