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Record W4399888965 · doi:10.4095/pwu5neguzc

Critical mineral resource potential of tailings from the former Saint Lawrence columbium mine, Oka, Quebec

2024· report· en· W4399888965 on OpenAlexaffabout
A. J. Desbarats, Michel Beauchamp, I Bilot, S. Madore, Matthew Polivchuk, M Wygergangs, J B Percival

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicTailings Management and Properties
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsTailingsMineral resource classificationSAINTMining engineeringGeologyMineralGeochemistryEnvironmental scienceMetallurgyHistoryMaterials science

Abstract

fetched live from OpenAlex

Between 1961 and 1976, the Saint Lawrence Columbium (SLC) mine produced pyrochlore concentrate and ferroniobium alloy from a carbonatite-hosted deposit near Oka, Quebec. Tailings generated by ore processing contain critical minerals including niobium (Nb), rare earth elements (REEs), and phosphorus (P). This report is concerned with characteristics of the tailings that could determine their critical mineral resource potential. It describes their physical properties, their mineralogy, and their bulk geochemistry. Split-spoon core samples were obtained at continuous downhole intervals from a single 25 m borehole penetrating the full thickness of the tailings impoundment. Grain-size distribution data for the tailings show that they range in texture from medium sand to predominantly clayey silt. The average density, water content, and porosity of the tailings are 2.82 g/cm3, 30%, and 47%, respectively. The mean plasticity index of the tailings is 11.3%. Based on historical mine production of about 5.7 million tonnes of ore, the 19.2 ha impoundment contains an estimated 3.8 million m3 of tailings material with an average thickness of 20 m. Bulk X-ray Diffraction (XRD) analyses show that the tailings are composed mainly of calcite (64-89 wt. %), biotite (6-17 wt.%), fluorapatite (2-22 wt.%), and chlorite (0-5 wt.%). Scanning Electron Microscopy (SEM) reveals that tailings also contain a considerable diversity of minor and trace gangue minerals including ferroan dolomite, nepheline, monticellite, richterite, pyrite, sphalerite, magnetite, perovskite, and pyrochlore. From a critical minerals perspective, the tailings are of interest for their unrecovered pyrochlore and apatite contents. Pyrochlore and apatite are the mineral hosts of Nb and P, respectively. However, Energy Dispersive Spectroscopy (EDS) and Electron Probe Microanalyses (EPMA) show that both pyrochlore and apatite are highly enriched in REE as well. Based on historical mine production figures and estimates of Nb recovery efficiency, the tailings contain 0.15 wt.% Nb2O5 or about 0.3wt.% pyrochlore. Based on XRD analyses of tailings samples conducted here, the average P2O5 and apatite contents of the tailings are 2.46 wt.% and 5 wt.%, respectively. Both pyrochlore and apatite exhibit similar REE enrichment distribution patterns dominated by light rare earth elements. Average total rare earth oxide (ΣREEO) in pyrochlore and apatite grains are in the ranges of 9.62 to 10.42 wt.% and 2.47 to 3.25 wt.%, respectively. Historical air photographs show that tailings disposal practices for the different waste streams from the SLC mill varied over the life of the mine. This is manifested by significant tailings heterogeneity observed in the stratigraphic borehole. Notably, near the base of the impoundment, a thin 2 m layer of dense, coarse-grained material contains up to 0.76 wt.% Nb2O5 and 7.74 wt.% P2O5 (or about 22% apatite) as well as abundant magnetite and sulfide minerals. Other depth horizons are dominated by fine-textured tailings containing abundant biotite and chlorite, which adversely affected mill recovery during mining operations. These factors highlight the need for systematic drilling of historical tailings impoundments in order to assess their critical mineral resource potential with confidence.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.162

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0090.001

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 head0.016
GPT teacher head0.230
Teacher spread0.215 · 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 designObservational
Domainnot available
GenreOther

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".

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Citations0
Published2024
Admission routes2
Has abstractyes

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