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Record W3013186402 · doi:10.1051/e3sconf/20199809026

Characterization study of As and Se in pyrites from two historic mines in British Columbia

2019· article· en· W3013186402 on OpenAlexaffabout
Jocelyn Ross-Lindeman, Dirk Kirste

Bibliographic record

VenueE3S Web of Conferences · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicArsenic contamination and mitigation
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsXANESPyriteSeleniumArsenicCharacterization (materials science)SulfurEnvironmental chemistrySynchrotronMineralogyMetallurgyChemistryMining engineeringMaterials scienceGeologyEnvironmental scienceNanotechnologySpectroscopy

Abstract

fetched live from OpenAlex

Arsenic (As) and selenium (Se) can be toxic if they occur as soluble species at elevated concentrations. One process that can mobilize these elements into the environment is the oxidation of As- and Se-containing pyrites. This study presents the initial mineralogical (XRD, SEM-EDS, LA-ICP-MS, and synchrotron micro-XRF and micro-XANES) characterization of As- and Se-pyrites from two historic mines in British Columbia, the Sullivan Mine and the Sunro Mine. Results show that As occurs in some of the pyrites from the Sullivan Mine; comparison of the micro-XANES measurements to published data suggests As substitutes for sulphur. Selenium is detected in pyrites from the Sunro Mine but this Se is slightly more oxidized than measured in previous studies on Se-pyrite and further investigation of these samples is required. Results from this characterization study will be incorporated into the next phase of research measuring element mobilization after oxidation reactions to identify the effects of As or Se substitution on these reactions.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.438
Threshold uncertainty score0.999

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)0.0020.000

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 head0.008
GPT teacher head0.218
Teacher spread0.210 · 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 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
Published2019
Admission routes2
Has abstractyes

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