Initialization of thermal models in cold and warm permafrost
Why this work is in the frame
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Bibliographic record
Abstract
Equilibrium modelling, also known as spin-up, is a technique for initializing a stable thermal regime in ground temperature models for permafrost regions. The results act as a baseline for subsequent transient analyses of ground temperature response to climate change or infrastructure. In practice, spin-up procedures are often loosely described or neglected, and the criteria by which a stable thermal regime is evaluated are rarely defined or presented explicitly. In this paper, model results show that no single criterion based on thresholds of inter-cycle temperature change can be used to identify a stable thermal regime in all spin-up scenarios. Results from simulations using a wide range of initialization temperatures and conditions show the number of spin-up cycles can range between 10 and 10 000, and a spin-up criterion as fine as 0.00001 °C/cycle is required to achieve a stable thermal regime suitable for deeper warm permafrost models. The implications of selected threshold criteria are examined in follow-up transient analyses and show that warm permafrost models can be highly sensitive to initial temperature profiles based on the criterion used. The results alert scientists and engineers to the importance of initialization on site-specific and regional permafrost models for transient ground temperature analyses.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 it