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Record W3089245582 · doi:10.1080/19236026.2020.1757985

Continuous electrocoagulation system for mining wastewater treatment

2020· article· en· W3089245582 on OpenAlexaff
A. Rodriguez-Prado

Bibliographic record

VenueCIM Journal · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicAdvanced oxidation water treatment
Canadian institutionsYukon University
Fundersnot available
KeywordsElectrocoagulationWastewaterEnvironmental scienceSewage treatmentWaste managementOil refineryProcess engineeringEnvironmental engineeringEngineering

Abstract

fetched live from OpenAlex

Electrocoagulation is an efficient method for mining, industrial, and municipal wastewater treatment. Investigations have primarily focused on batch systems, while optimizing electrical current and operational time for maximum contaminant removal. Applying the correct amount of current in continuous systems is challenging due to varying water quality and residence time. A continuous laboratory-scale electrocoagulation system was investigated for treatment of ore- and petroleum-processing wastewater. The power to the cell was wired to a control loop feedback system. Preliminary results indicated that contaminants were removed by a minimum of 29% for ore-processing metals and 99% for petroleum hydrocarbons. Additional investigation is granted to study control settings that provide the optimal amount of ions into the electrocoagulation system for specific mining wastewater treatment applications.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.021
GPT teacher head0.238
Teacher spread0.217 · 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 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
Published2020
Admission routes1
Has abstractyes

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