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Record W1580794370 · doi:10.3390/resources4030524

Geothermal Energy Potential in Low Enthalpy Areas as a Future Energy Resource: Identifying Feasible Targets, Quebec, Canada, Study Case

2015· article· en· W1580794370 on OpenAlexaffabout
Jacek Majorowicz, Vasile Minea

Bibliographic record

VenueResources · 2015
Typearticle
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsHydro-Québec
Fundersnot available
KeywordsGeologySedimentary rockAquiferGeothermal gradientStructural basinSedimentary basinBasementGeothermal energyGeochemistryHydrology (agriculture)GeomorphologyGroundwaterPaleontologyArchaeologyGeotechnical engineeringGeography

Abstract

fetched live from OpenAlex

Heat flow of the sedimentary succession of the Eastern Canada Sedimentary Basins varies from 40 mW/m2 close to the exposed shield in the north to high 60–70 mW/m2 in the southwest–northeast St. Lawrence corridor. As high fluid flow rates are required for a successful geothermal application, the most important targets are deep existing permeable aquifers rather than hard rock, which would need to be fracked. Unfortunately, the ten most populated Québec urban centers are in the areas where the Grenville (Canadian Shield) is exposed or at shallow depths with sedimentary cover where temperatures are 30 °C or less. The city of Drummondville will be the exception, as the basement deepens sharply southwest, and higher temperatures reaching >120 °C are expected in the deep Cambrian sedimentary aquifers near a 4–5-km depth. Deep under the area where such sediments could be occurring under Appalachian nappes, temperatures significantly higher than 140 °C are predicted. In parts of the deep basin, temperatures as high as 80 °C–120 °C exist at depths of 3–4 km, mainly southeast of the major geological boundary: the Logan line. There is a large amount of heat resource at such depths to be considered in this area for district heating.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.303

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.011
GPT teacher head0.227
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2015
Admission routes2
Has abstractyes

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