MétaCan
Menu
Back to cohort
Record W1982565300 · doi:10.1080/09593330.2012.660648

Counter-current acid leaching process for copper azole treated wood waste

2012· article· en· W1982565300 on OpenAlex

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

VenueEnvironmental Technology · 2012
Typearticle
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsFPInnovationsInstitut National de la Recherche ScientifiqueUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaFPInnovations
KeywordsLeaching (pedology)CopperLeachatePulp and paper industryEffluentSlurryAnodeChemistryCopper extraction techniquesWaste managementMetallurgyEnvironmental scienceEnvironmental chemistryMaterials scienceEnvironmental engineeringElectrodeSoil water

Abstract

fetched live from OpenAlex

This study explores the performance of a counter-current leaching process (CCLP) for copper extraction from copper azole treated wood waste for recycling of wood and copper. The leaching process uses three acid leaching steps with 0.1 M H2SO4 at 75degrees C and 15% slurry density followed by three rinses with water. Copper is recovered from the leachate using electrodeposition at 5 amperes (A) for 75 min. Ten counter-current remediation cycles were completed achieving > or = 94% copper extraction from the wood during the 10 cycles; 80-90% of the copper was recovered from the extract solution by electrodeposition. The counter-current leaching process reduced acid consumption by 86% and effluent discharge volume was 12 times lower compared with the same process without use of counter-current leaching. However, the reuse of leachates from one leaching step to another released dissolved organic carbon and caused its build-up in the early cycles.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.165
Threshold uncertainty score0.572

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 head0.013
GPT teacher head0.259
Teacher spread0.246 · 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