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Record W3127044564 · doi:10.3390/en14030706

Deep Geothermal Heating Potential for the Communities of the Western Canadian Sedimentary Basin

2021· article· en· W3127044564 on OpenAlexafffundabout
Jacek Majorowicz, Stephen E. Grasby

Bibliographic record

VenueEnergies · 2021
Typearticle
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsGeological Survey of CanadaUniversity of Alberta
FundersHelmholtz-Alberta InitiativeUniversity of Alberta
KeywordsGeothermal gradientStructural basinForeland basinGeologySedimentary rockAquiferSedimentary basinGeothermal energyArchaeologyHydrology (agriculture)GeomorphologyGeochemistryGroundwaterPaleontologyGeography

Abstract

fetched live from OpenAlex

We summarize the feasibility of using geothermal energy from the Western Canada Sedimentary Basin (WCSB) to support communities with populations >3000 people, including those in northeastern British Columbia, southwestern part of Northwest Territories (NWT), southern Saskatchewan, and southeastern Manitoba, along with previously studied communities in Alberta. The geothermal energy potential of the WCSB is largely determined by the basin’s geometry; the sediments start at 0 m thickness adjacent to the Canadian shield in the east and thicken to >6 km to the west, and over 3 km in the Williston sub-basin to the south. Direct heat use is most promising in the western and southern parts of the WCSB where sediment thickness exceeds 2–3 km. Geothermal potential is also dependent on the local geothermal gradient. Aquifers suitable for heating systems occur in western-northwestern Alberta, northeastern British Columbia, and southwestern Saskatchewan. Electrical power production is limited to the deepest parts of the WCSB, where aquifers >120 °C and fluid production rates >80 kg/s occur (southwestern Northwest Territories, northwestern Alberta, northeastern British Columbia, and southeastern Saskatchewan. For the western regions with the thickest sediments, the foreland basin east of the Rocky Mountains, estimates indicate that geothermal power up to 2 MWel. (electrical), and up to 10 times higher for heating in MWth. (thermal), are possible.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.143

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.215
Teacher spread0.203 · 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 designSimulation or modeling
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

Citations27
Published2021
Admission routes3
Has abstractyes

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