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Record W3135249028 · doi:10.3390/min11030259

Active Treatment of Contaminants of Emerging Concern in Cold Mine Water Using Advanced Oxidation and Membrane-Related Processes: A Review

2021· review· en· W3135249028 on OpenAlex
Sébastien Ryskie, Carmen Mihaela Neculita, Éric Rosa, Lucie Coudert, Patrice Couture

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMinerals · 2021
Typereview
Languageen
FieldEnvironmental Science
TopicMine drainage and remediation techniques
Canadian institutionsInstitut National de la Recherche ScientifiqueUniversité du Québec en Abitibi-Témiscamingue
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsEnvironmental scienceWater treatmentContaminationCold climateSalinityWater cycleEnvironmental engineeringEcologyGeologyBiology

Abstract

fetched live from OpenAlex

Responsible use and effective treatment of mine water are prerequisites of sustainable mining. The behavior of contaminants in mine water evolves in relation to the metastable characteristics of some species, changes related to the mine life cycle, and mixing processes at various scales. In cold climates, water treatment requires adaptation to site-specific conditions, including high flow rates, salinity, low temperatures, remoteness, and sensitivity of receiving waterbodies. Contaminants of emerging concern (CECs) represent a newer issue in mine water treatment. This paper reviews recent research on the challenges and opportunities related to CECs in mine water treatment, with a focus on advanced oxidation and membrane-based processes on mine sites operating in cold climates. Finally, the paper identifies research needs in mine water treatment.

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.

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: Review · Consensus signal: Review
Teacher disagreement score0.722
Threshold uncertainty score0.646

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.040
GPT teacher head0.337
Teacher spread0.297 · 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