Deep vs. shallow controlling factors of the crustal thermal field – insights from 3D modelling of the<scp>B</scp>eaufort‐<scp>M</scp>ackenzie<scp>B</scp>asin (<scp>A</scp>rctic<scp>C</scp>anada)
Bibliographic record
Abstract
Abstract Significant lateral variations in observed temperatures in theBeaufort‐MackenzieBasin raise the question on the temperature‐controlling factors. Based on the structural configuration of the sediments and underlying crust in the area, we calculate the steady‐state 3D conductive thermal field. Integrated data include the base of the relic permafrost layer representing the 0 °C‐isotherm, public‐domain temperature data (from 227 wells) and thermal conductivity data. For >75% of the wells the predicted temperatures deviate by <10 K from the observed temperatures, which validates the overall model setup and adopted thermal properties. One important trend reproduced by the model is a decrease in temperatures from the western to the eastern basin. While in the west, a maximum temperature of 185 °C is reached at 5000 m below sea level, in the east the maximum temperature is 138 °C. The main cause for this pattern lies in lateral variations in thermal conductivity indicating differences in the shale and sand contents of the different juxtaposed sedimentary units. North‐to‐south temperature trends reveal the superposition of deep and shallow effects. At the southern margin, where the insulating effect of the low‐conductive sediments is missing, temperatures are lowest. Farther north, where the sub‐sedimentary continental crust is thick enough to produce considerable heat and a thick pile of sediments efficiently stores heat, temperatures tend to be highest. Temperatures decrease again towards the northernmost distal parts of the basin, where thinned continental and oceanic crust produce less radiogenic heat. Wells with larger deviations of the purely conductive model from the temperature observations (>15 K at 10% of the wells) and their basin‐wide pattern of misfit tendency (too cold vs. too warm temperature predictions) point to a locally restricted coupling of heat transport to groundwater flow.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".