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Record W2982258468 · doi:10.4095/224673

Sphalerite and kimberlite indicator minerals in till from the Zama Lake region, northwest Alberta (NTS 84L and 84M)

2008· report· en· W2982258468 on OpenAlexaffabout
A Plouffe, R C Paulen, I R Smith, I M Kjarsgaard

Bibliographic record

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

Abstract

fetched live from OpenAlex

This report presents the results and interpretations of the heavy mineral assemblages and pebble lithologies of 19 bulk till samples collected in northwest Alberta, from the region of a sphalerite dispersal train originally reported by Plouffe et al. (2006a). Indurated pebbles in the 4-8 mm sized fraction of till dominantly consist of distally-derived bedrock lithologies: Canadian Shield rocks, Paleozoic carbonates, and quartzite. Three till samples contain mineralized clasts with visible pyrite and marcasite. Kimberlite indicator minerals (KIMs) in till, including Cr-pyrope, Cr-diopside and chromite are present in trace amounts (1 to 2 grains) in nine samples. Although the KIM counts are low, the samples with KIMs do cluster in the Zama Lake - Zama City area. The source, proximal or distal, is unknown and remains to be identified. Seven out of the 19 till samples contain sand-sized sphalerite grains, with the strongest anomaly consisting of 989 sphalerite grains recovered from a 34 kg till sample. The sphalerite is dominantly in the 0.25 to 0.5 mm fraction (900 grains) with smaller amounts (89 grains) in the 0.5 to 1.0 mm size range. The new data indicate that the sphalerite dispersal train first identified by Plouffe et al. (2006a) could cover an area of over 4000 km2. The bedrock source(s) of the sphalerite in till remains to be discovered.

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 score0.112
Threshold uncertainty score0.225

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.231
Teacher spread0.207 · 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

Citations4
Published2008
Admission routes2
Has abstractyes

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