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Record W4404360433 · doi:10.1002/jrs.6748

Assessment of Time‐Gated Raman Spectroscopy for Online Mineralogy of a Spodumene Ore

2024· article· en· W4404360433 on OpenAlexafffundabout
M. Legault, Satu Ojala, Jean‐François Boulanger

Bibliographic record

VenueJournal of Raman Spectroscopy · 2024
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsUniversité du Québec en Abitibi-Témiscamingue
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsRaman spectroscopySpodumeneMineralogyMineralAnalytical Chemistry (journal)GeologyChemistryMaterials scienceMetallurgyEnvironmental chemistryPhysicsOpticsCeramic

Abstract

fetched live from OpenAlex

ABSTRACT This paper investigates the applicability of time‐gated Raman spectroscopy (TRS) for online mineralogy identification, focusing on a Li‐bearing spodumene ore. The study provides an overview of existing online mineralogy tools and points out some limitations of elemental analysis techniques. Dense media separation concentrate and tailing samples used originated from a deposit in Quebec, Canada. Various techniques, including ICP‐AES, XRD, laser diffraction, and specific gravity determination, were used for detailed sample characterization. Samples and their mixtures at known ratios were prepared as powder and slurries, before being analyzed using TRS, followed by spectrum quantitative analysis. Results show a linear correlation between spodumene percentage by weight and the main Raman peak height or area, in both dry and slurry form, with a higher determination coefficient in slurry form. TRS also provided indications as to the gangue minerals present in the samples. This study shows the potential for TRS as a tool for online mineralogical assessment of spodumene ores, and further work should target the determination of detection limits and quantification of both valuable and gangue minerals.

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)0.001
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: Empirical
Teacher disagreement score0.108
Threshold uncertainty score0.756

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.012
GPT teacher head0.303
Teacher spread0.291 · 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 designBench or experimental
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

Citations2
Published2024
Admission routes3
Has abstractyes

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