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Record W2908564810 · doi:10.4095/222108

Geological assessment of known Zn-Pb showings, Mackenzie Mountains, Northwest Territories

2006· report· en· W2908564810 on OpenAlexaffabout
Keith Dewing, Rachel Sharp, Luke Ootes, E C Turner, Sarah A. Gleeson

Bibliographic record

Venuenot available
Typereport
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsGeologyArchaeologyGeography

Abstract

fetched live from OpenAlex

The Mackenzie Mountains have more than 100 Zn-Pb showings. The objectives of the 2005 fieldwork were 1) to assess showings from a wide geographic area and stratigraphic range, 2) verify the assessment files, and 3) rank the showings on exploration potential. TIC, ART-EKWI, BEAR, ICE, KEG, RAIN, TAP, AB, and GAYNA were visited. Most of the showings are hosted in fractures with minor brecciation and very rarely, carbonate replacement. The main economic minerals are sphalerite and galena, but copper sulphide minerals are commonly present. Gangue minerals include dolomite, calcite, quartz, barite, and fluorite. The best targets for further exploration are considered to be showings hosted in strata that were limestone (at the time of mineralization) rather than dolostone; that exhibit strong chemical interaction between the host rock and fluid resulting in carbonate dissolution or replacement; and that have multiple generations of sphalerite and galena. BEAR, GAYNA, AB, and TIC are considered the most attractive exploration targets.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.615
Threshold uncertainty score0.765

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.025
GPT teacher head0.288
Teacher spread0.263 · 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

Citations8
Published2006
Admission routes2
Has abstractyes

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