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Record W2187543632 · doi:10.4095/213201

Progress report of EXTECH-IV seismic investigations in the Athabasca Basin, Saskatchewan-Alberta

2002· book· en· W2187543632 on OpenAlexaffabout
Don White, Z. Hajnal, E. Adam, Gilles Bellefleur, Brian J. Roberts, B. Reilkoff, David N. Jamieson, Susanne Woelz, R Koch, Brian F. Powell, I R Annesley, Douglas R. Schmitt

Bibliographic record

Venuenot available
Typebook
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsGeologyStructural basinOil sandsMining engineeringGeographyArchaeologyPaleontologyAsphalt

Abstract

fetched live from OpenAlex

EXTECH-IV is a multidisciplinary study designed to improve the geoscience framework and develop exploration technology for unconformity-type uranium deposits of the Athabasca Basin. A multi-element seismic reflection program was conducted in the vicinity of the McArthur River uranium mining camp to test this technology for imaging the subsurface geometry of the ore deposits and the geology that hosts them. The seismic program consisted of 2-D reflection profiling (39 km of regional and 8 km of high resolution), a limited 3-D high-resolution survey, and vertical seismic profiling. Results from preliminary processing of the high-resolution 2-D seismic and vertical seismic profiling data show: 1) laterally continuous reflectivity regionally associated with the basement unconformity beneath the basin-fill sediments; 2) local reflectivity within individual units of the Manitou Falls Formation that is generally comparable to reflectivity of the boundaries between the formation members; and 3) local strong reflectivity associated with an abrupt increase in density that occurs within the Manitou Falls b member.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score0.253

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.015
GPT teacher head0.219
Teacher spread0.205 · 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
Published2002
Admission routes2
Has abstractyes

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