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Record W2083928453 · doi:10.1190/1.2369749

Advances in airborne EM acquisition and processing for uranium exploration in the Athabasca Basin, Canada

2006· article· en· W2083928453 on OpenAlexaffabout
Richard Irvine, Ken Witherly

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysical and Geoelectrical Methods
Canadian institutionsCondor Petroleum (Canada)
Fundersnot available
KeywordsGeologyArcheanBasementUraniumStructural basinElectromagneticsProterozoicMagnetotelluricsElectrical conductorMining engineeringRemote sensingEarth scienceGeochemistryGeomorphologySeismologyTectonicsElectrical resistivity and conductivityArchaeologyEngineeringEngineering physicsElectrical engineering

Abstract

fetched live from OpenAlex

Uranium deposits in the Athabasca Basin, northern Canada, are associated with graphitic metasediments and faults zones in the Archean basement and are often “blind”, covered by hundreds of meters of resistive Proterozoic sandstones. Hence airborne electromagnetics (EM) is commonly used in initial exploration over large areas. In recent years new airborne EM systems have become commercially available which have the capability to detect large graphitic zones in or near the basement at depths approaching 1000 m, examples of which are in this paper. Conductivity depth inversions and forward modeling of graphitic conductors in a conductive half-space are important tools in interpretation as they provide quantitative confirmation that deep conductors are responsible for the observed responses.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.177
Threshold uncertainty score0.357

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.010
GPT teacher head0.222
Teacher spread0.213 · 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

Citations3
Published2006
Admission routes2
Has abstractyes

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