Permafrost distribution modelling in the semi-arid Chilean Andes
Bibliographic record
Abstract
Abstract. Mountain permafrost and rock glaciers in the dry Andes are of growing interest due to the increase in mining industry and infrastructure development in this remote area. Empirical models of mountain permafrost distribution based on rock glacier activity status and temperature data have been established as a tool for regional-scale assessments of its distribution; this kind of model approach has never been applied for a large portion of the Andes. In the present study, this methodology is applied to map permafrost favourability throughout the semi-arid Andes of central Chile (29–32° S), excluding areas of exposed bedrock. After spatially modelling of the mean annual air temperature distribution from scarce temperature records (116 station years) using a linear mixed-effects model, a generalized additive model was built to model the activity status of 3524 rock glaciers. A permafrost favourability index (PFI) was obtained by adjusting model predictions for conceptual differences between permafrost and rock glacier distribution. The results indicate that the model has an acceptable performance (median AUROC: 0.76). Conditions highly favourable to permafrost presence (PFI ≥ 0.75) are predicted for 1051 km2 of mountain terrain, or 2.7 % of the total area of the watersheds studied. Favourable conditions are expected to occur in 2636 km2, or 6.8 % of the area. Substantial portions of the Elqui and Huasco watersheds are considered to be favourable for permafrost presence (11.8 % each), while in the Limarí and Choapa watersheds permafrost is expected to be mostly limited to specific sub-watersheds. In the future, local ground-truth observations will be required to confirm permafrost presence in favourable areas and to monitor permafrost evolution under the influence of climate change.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".