Bibliographic record
Abstract
The key element in the characterization, assessment and development of geothermal energy systems is the resource type. Throughout the past 30 years many resource type schemes and definitions were published, based on temperature and thermodynamic properties. An alternative possibility to cataloging geothermal energy systems is by their geologic characteristics, referred to as geothermal plays. Applied to worldwide case studies, a new catalog is developed based on the effects of geological controls and structural plate tectonic positions on thermal regime and heat flow, hydrogeologic regime, fluid dynamics, fluid chemistry, faults and fractures, stress regime, and lithological sequence. Understanding geologic controls, especially of geothermal plays without surface expression, allows the comparison with hydrocarbon reservoirs through their ratio of porosity and permeability. This analog has implications on site-specific, first class exploration strategies and reservoir improvement through technologies specifically suitable for unconventional sustainable energy reservoirs. This article aims to introduce geothermal plays to a wide geoscientific community and to initiate a geologically based cataloging of geothermal resources. With this new catalog of geothermal plays, it will be ultimately possible to transfer lessons learned not only within one specific catalog type, but also technology from geothermal plays to unconventional hydrocarbon plays and vice versa.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.020 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".