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Record W3153638019 · doi:10.1130/g48587.1

A metasedimentary source of gold in Archean orogenic gold deposits

2021· article· en· W3153638019 on OpenAlexaffabout
Iain Pitcairn, Nikolaos Leventis, Georges Beaudoin, Stéphane Faure, Carl Guilmette, B Dubé

Bibliographic record

VenueGeology · 2021
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsGeological Survey of CanadaUniversité Laval
Fundersnot available
KeywordsArcheanGeologyGeochemistryGreenstone beltMetamorphismMetamorphic rockMonaziteSedimentary rockZircon

Abstract

fetched live from OpenAlex

Abstract The sources of metals enriched in Archean orogenic gold deposits have long been debated. Metasedimentary rocks, which are generally accepted as the main metal source in Phanerozoic deposits, are less abundant in Archean greenstone belts and commonly discounted as a viable metal source for Archean deposits. We report ultralow-detection-limit gold and trace-element concentrations from a suite of metamorphosed sedimentary rocks from the Abitibi belt and Pontiac subprovince, Superior Province, Canada. Systematic decreases in the Au content with increasing metamorphic grade indicate that Au was mobilized during prograde metamorphism. Mass balance calculations show that over 10 t of Au, 30,000 t of As, and 600 t of Sb were mobilized from 1 km3 of Pontiac subprovince sedimentary rock metamorphosed to the sillimanite metamorphic zone. The total gold resource in orogenic gold deposits in the southern Abitibi belt (7500 t Au) is only 3% of the Au mobilized from the estimated total volume of high-metamorphic-grade Pontiac sedimentary rock in the region (25,000 km3), indicating that sedimentary rocks are a major contributor of metals to the orogenic gold deposits in the southern Abitibi belt.

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 score0.192
Threshold uncertainty score0.381

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 studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.014
GPT teacher head0.222
Teacher spread0.208 · 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

Citations66
Published2021
Admission routes2
Has abstractyes

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