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Record W2909382515 · doi:10.4095/215381

Electrical conductivity mechanism and textures of mineralized sericite schist from the Gold Lake area of the Yellowknife mining district, Northwest Territories

2004· report· en· W2909382515 on OpenAlexaffabout
S Connell-Madore, P. A. Hunt

Bibliographic record

Venuenot available
Typereport
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsSericiteSchistGeologyGeochemistryMining engineeringMineralogyArchaeologySeismologyMetamorphic rockGeography

Abstract

fetched live from OpenAlex

The electrical conductivity mechanisms have been determined for five subsamples taken from two mineralized schist samples collected from the Gold Lake area of the Yellowknife mining district, Northwest Territories. The samples were selected to characterize the resistivity of the alteration zone, determine the effect of crosscutting veins, and of fine-grained sulphide minerals oriented parallel to foliation. The purpose of this paper is to document, within the framework of the Yellowknife EXTECH-III Project, results of the laboratory electrical resistivity determinations for use in interpreting ground electromagnetic surveys which have been conducted in the Gold Lake area. Results indicate that high bulk electrical resistivity (?r) values are likely a result of poor sulphide grain connectivity and of fairly continuous quartz and calcite layers. The lower ?r values are due to good sulphide grain connectivity. Alteration visible in hand sample and in scanning electron microscope images suggest that the effect of some pore-fluid conductivity exists as well.

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 score0.962
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.229
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
Published2004
Admission routes2
Has abstractyes

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