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Record W4233651070 · doi:10.2202/1934-2659.1047

A Generalized Kinetic Model for Hydrometallurgical Processes

2007· article· en· W4233651070 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.

Bibliographic record

VenueChemical Product and Process Modeling · 2007
Typearticle
Languageen
FieldEngineering
TopicMetal Extraction and Bioleaching
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsReagentElectrochemistryLeaching (pedology)MetalDissolutionElectronIonMaterials scienceKinetic energyInorganic chemistrySemiconductorElectron transferCathodic protectionSolid solutionConductorAnodeChemistryMetallurgyPhysical chemistryElectrodeComposite materialPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

In electrochemical leaching processes the solid must be an electric conductor, e.g., a metal, or a semiconductor, e.g., certain metal sulfides or oxides. Reaction takes place by the transfer of electrons at the solid surface and involves oxidation–reduction processes that take place simultaneously at two different locations not far from each other. At one location, electrons are picked up by a depolarizer, D, in solution, e.g., O2, H+, etc. (the cathodic zone) and at another location metal ions are released in solution (the anodic zone) where they react with reagent C. A single kinetic law derived theoretically is obeyed: Rate = k1k2A[D][C] / (k1[D] + k2[C]) where k1 and k2 are constants, and A is the total surface area of the dissolving solid.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.390
Threshold uncertainty score0.629

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 head0.035
GPT teacher head0.277
Teacher spread0.241 · 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