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Record W2979387129 · doi:10.4095/314918

Geoenvironmental characteristics of gold and critical metal deposits

2019· report· en· W2979387129 on OpenAlexaffabout
Michael B. Parsons

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicMetal Extraction and Bioleaching
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsMetalGeologyEnvironmental scienceMining engineeringMaterials scienceMetallurgy

Abstract

fetched live from OpenAlex

The Critical Metals Activity used detailed geochemical, mineralogical, and limnological methods to characterize processes controlling the mobility of trace elements and radionuclides in mine wastes and waters at the abandoned St. Lawrence Columbium (SLC) Mine in Oka, Quebec. This mine operated from 1961 to 1976 and at the time was one of the largest niobium (Nb) producers in the world. Geologically, the SLC Mine is very similar to several other carbonatite-hosted mineral deposits across Canada that are being considered for mining of elements used in green energy and high-tech applications, including Nb and rare earth elements (REE). These studies have generated new geoscience knowledge on the potential environmental impacts of mining critical metals and have been used by the Québec Ministère de l'Energie et des Ressources Naturelles (MERN) to help guide remediation decisions for the SLC Mine site. The results will also help industry and regulators to improve environmental predictions for future Nb- and REE-mining projects and to support the development of new environmental guidelines. The Northern Baselines (Geoscience Tools for Environmental Assessment of Metal Mining) Activity used a multidisciplinary geochemical, paleolimnological, micropaleontological, and traditional knowledge approach to produce new geoscience knowledge on baseline geochemistry and cumulative impacts of geogenic and anthropogenic processes, particularly climate variability, on the transport and fate of metal(loid)s in mineralized regions of northern Canada. New geoscience knowledge on the role of climate variability on speciation of arsenic in porewater and sediments, and the seasonal cycling of metalloids between surface waters and sediments has implications for Environmental Assessment, remediation of contaminated sites, including Crown lands, and new development. The activity also generated new knowledge on the impacts of 21st century climate change on long-term carbon dynamics in permafrost wetlands, important for understanding feedback mechanisms and global carbon cycling.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.718
Threshold uncertainty score0.643

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)0.0000.000

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 head0.020
GPT teacher head0.254
Teacher spread0.234 · 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 designOther design
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
Published2019
Admission routes2
Has abstractyes

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