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Record W2791498527 · doi:10.1002/cjce.23175

Analytical and semi‐analytical kinetics models for design and optimization of double‐resistance resin in pulp and carbon in pulp processes with both reversible and irreversible nature

2018· article· en· W2791498527 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicMaterial Properties and Processing
Canadian institutionsnot available
Fundersnot available
KeywordsPulp (tooth)AdsorptionUraniumThermal diffusivityChemistryMaterials scienceThermodynamicsProcess engineeringPulp and paper industryComputer scienceMetallurgyOrganic chemistryEngineeringPhysics

Abstract

fetched live from OpenAlex

Abstract The current study was aimed at developing a package of “model + algorithm” for the design of resin in pulp (RIP) and carbon in pulp (CIP) processes of gold, uranium, and base metals. For this purpose, we first formulated a double‐resistance model for irreversible adsorption (accompanied by chemical reaction) in CSTRs, and modified the McKay et al. semi‐analytical model for reversible uptake in a similar system. We then devised two algorithms for the design and optimization of reversible and irreversible RIP and CIP cascades. The developed algorithms were applied on the extraction of copper, uranium, and gold. The packages are able to specify the optimum number of stages, reactor volume (V), resin flow rate (m . ), and resin hold up (φ s ). This shows an evident advantage over the McCabe‐Thiele method, whose only result is the number of stages. The new methods have only two adjustable parameters of diffusivity (D eff ) and liquid film coefficient (k), whose determination can be carried out through simple batch experiments. As an additional work, this study also presents a method for mathematical troubleshooting for the Mc Kay et al. model.

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 score0.009
Threshold uncertainty score0.338

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 head0.194
Teacher spread0.181 · 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