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Record W2023794680 · doi:10.3997/2214-4609.20140973

Athabasca Regional Geophysical Study - Implications for Geothermal Development in Northeastern Alberta, Canada

2014· article· en· W2023794680 on OpenAlexaffabout
Elahe P. Ardakani, Douglas R. Schmitt

Bibliographic record

VenueProceedings · 2014
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGeologyGeothermal gradientPrecambrianBasementGeothermal explorationSedimentary rockLineamentGeologic mapGeochemistryEarth scienceStructural basinGeothermal energyMetamorphic rockRegional geologyMining engineeringGeomorphologyTectonicsSeismologyGeophysicsVolcanism

Abstract

fetched live from OpenAlex

Summary Athabasca region in northeastern Alberta hosts many producing oil sand projects. These projects require large amounts of thermal energy to produce most of which is currently provided by burning natural gas; and this increases the greenhouse gas footprint to producing such hydrocarbons. One possible solution is to instead use geothermal heat directly with hot fluids produced using Engineered Geothermal Systems (EGS). Geothermal exploration always starts with broad geological structure reconnaissance of the area. Seismic reflection profiles, High Resolution Aeromagnetic (HRAM) data, and a large amount of available well-logs are used in an integrated approach to outlining sedimentary basin, mapping geological formation tops, locating fault zones and other structural lineaments, finding true depth of metamorphic basement, and finally building a detailed geological model of the region. The 3D geological model is constructed using these available data that reveals some detail about the gross structure of the region. This model shows that the Precambrian basement surface is a smoothly undulating surface that could be consistent with minor faulting. The topography of this surface affects the structure of overlying sedimentary formations.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.597
Threshold uncertainty score0.946

Codex and Gemma teacher scores by category

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

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 head0.013
GPT teacher head0.215
Teacher spread0.202 · 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 teacher head, 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
Published2014
Admission routes2
Has abstractyes

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