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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 OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.481
Threshold uncertainty score0.764

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.031
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