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Record W2897699302 · doi:10.1080/25726838.2018.1516935

Carbonatites: related ore deposits, resources, footprint, and exploration methods

2018· article· en· W2897699302 on OpenAlexaff
George J. Simandl, S J Paradis

Bibliographic record

VenueApplied Earth Science Transactions of the Institutions of Mining and Metallurgy · 2018
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsUniversity of VictoriaNatural Resources CanadaGeological Survey of Canada
FundersBritish Geological Survey
KeywordsCarbonatiteGeologyGeochemistryIgneous rockDikeLavaSilicateVolcano

Abstract

fetched live from OpenAlex

Most carbonatites were emplaced in continental extensional settings and range in age from Archean to recent. They commonly coexist with alkaline silicate igneous rocks, forming alkaline-carbonatite complexes, but some occur as isolated pipes, sills, dikes, plugs, lava flows, and pyroclastic blankets. Incorporating cone sheets, ring dikes, radial dikes, and fenitisation-type halos into an exploration model and recognising associated alkaline silicate igneous rocks increases the footprint of the target. Undeformed complexes have circular, ring, or crescent-shaped aeromagnetic and radiometric signatures. Carbonatites can be effectively detected by soil, till, and stream-sediment geochemical surveys, as well as biogeochemical and indicator mineral surveys Carbonatites and alkaline-carbonatite complexes are the main sources of rare earth elements (REE) and Nb, and host significant deposits of apatite, vermiculite, Cu, Ti, fluorite, Th, U, natural zirconia, and Fe. Nine per cent of carbonatites and alkaline-carbonatite complexes contain active or historic mines, making them outstanding multi-commodity 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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.031
GPT teacher head0.271
Teacher spread0.240 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations185
Published2018
Admission routes1
Has abstractyes

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