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Record W4383226415 · doi:10.12775/bgeo-2023-0003

Shallow geothermal heat in Western Canada: climatic warming impact changes with time– depth

2023· article· en· W4383226415 on OpenAlexafffundabout
Jacek Majorowicz, Jan Šаfanda

Bibliographic record

VenueBulletin of Geography Physical Geography Series · 2023
Typearticle
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsUniversity of Alberta
FundersHelmholtz-Alberta InitiativeUniversity of Alberta
KeywordsGeothermal gradientClimate changeStructural basinGeothermal heatingHeat flowGeologyDrillingGlobal warmingHeat fluxEnvironmental scienceClimatologyHydrology (agriculture)Geothermal energyHeat transferGeomorphologyGeographyMeteorologyThermalOceanographyGeophysicsGeotechnical engineering

Abstract

fetched live from OpenAlex

Gain of heat and temperature in the shallow subsurface over the last decades/century has been impacted by the industrial period climatic surface air temperature (SAT) increase. Detailed study of the available temperature-depth data based on 43 wells with single and repeated temperature logs done by the first author has been combined with data base information (Jessop et al 2005) to create temperature maps at depth. Based on these 43 logs it is shown that the heat flux increases with depth in most cases for the available depth data range from surface to some 200m. Model of heat flow versus depth based on the surface air temperature changes through the industrial epoque climatic warming explains the data. Spatial and depth distribution of available temperature and heat gain through the provinces of the Western Canadian Sedimentary Basin WCSB shows that drilling closer to surface is more economic than deeper to 50-100m.

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)0.000
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 score0.018
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.213
Teacher spread0.206 · 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

Citations0
Published2023
Admission routes3
Has abstractyes

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