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Predictive model of Li-Cs-Ta pegmatite deposits

2025· dataset· en· W7083014951 on OpenAlexaboutno aff

Bibliographic record

VenueGEOSCAN · 2025
Typedataset
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsPegmatiteNatural (archaeology)Geospatial analysisDeep learningData processingMaximum likelihood

Abstract

fetched live from OpenAlex

This model is derived from geological and geophysical data, which is processed using deep learning and natural language processing techniques. Displayed is a Pan-Canadian probability map indicating the likelihood of discovering next-generation lithium-cesium-tantalum (LCT) pegmatites. This map was generated using known Canadian LCT pegmatites and their associated geospatial features, incorporating geological and geophysical data analyzed through deep learning and natural language processing techniques. Higher probability values highlight areas with an increased likelihood of hosting next-generation deposits, making this map a valuable tool for decision-making.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.122
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.010
GPT teacher head0.221
Teacher spread0.211 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2025
Admission routes1
Has abstractyes

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Same venueGEOSCANSame topicGeochemistry and Geologic MappingFrench-language works237,207