Using Thermal Springs to Quantify Deep Groundwater Flow and Its Thermal Footprint in the Alps and a Comparison With North American Orogens
Bibliographic record
Abstract
Abstract The extent of deep groundwater flow in mountain belts and its thermal effects are uncertain. Here, we use a new database of discharge, temperature, and composition of thermal springs in the Alps to estimate the extent of deep groundwater flow and its contribution to the groundwater and heat budget. The results indicate that thermal springs are fed exclusively by meteoric water and make up 0.1% of the total groundwater budget. Spring water circulates on average to a depth of at least 2 km. The net heat extracted from the subsurface equals 1% of the background heat flow, which equals an average thermal footprint of 7 km2. Cooling by downward flow and heating by upward flow are three and two times higher than the net heat flow, respectively. Comparison with North American orogens shows that hydrothermal activity is higher in areas with high relief or areas under extension.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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 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".