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Record W6891724482 · doi:10.48380/dggv-d41a-4f49

Occurrences and mineralogy of lithium pegmatite in eastern Canada and for example the Georgia Lake pegmatite in more detail

2021· article· en· W6891724482 on OpenAlexaboutno aff

Bibliographic record

Venuedggv-e-publications · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPegmatiteMineralLithium (medication)PyroxeneMineral explorationMineral resource classification

Abstract

fetched live from OpenAlex

Eastern Canada hosts several occurrences of lithium pegmatite, which have recently come into the focus of exploration activities and detailed studies. Driven by the current and expected future demand for Li, the mineral occurrences are targeted by exploration companies. This area in Canada is currently in the focus for targeting the mineral occurrences of lithium pegmatite. The majority of the pegmatite are hosted in metasediments or biotite-rich granite. In the more northern part the host rock becomes also greenstone. These pegmatite are very old up to 2.6 billion years old. The latest update of the exploration data and statistical modelling combined with a more detail mine plan some new results will be presented for some of the Georgia lake pegmatite. The lithium mineralisation in these pegmatite is in many cases the spodumen. This light green pyroxene is often bid as an finger and builds up to 20 % of the volume of the pegmatite. In addition, previous work also identified beryl, columbite, molybdenite, amblygonite, apatite, and bityite, enhancing the Li and rare metals potential of the area. The pegmatite has different thickness and length. The bigger ones are up to a mile long and in some cases up to 20 m wide. Sometimes they split up in parallel dikes. The Li2O contend of the pegmatite varying from 0 up to 2,7 %. During the investigation some million tonnes of resources were defined with an average Li2O contend of around 1 %.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.599
Threshold uncertainty score0.801

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 science0.0000.000
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 head0.026
GPT teacher head0.226
Teacher spread0.199 · 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.

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

Citations0
Published2021
Admission routes1
Has abstractyes

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