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Record W2904344060 · doi:10.1002/cjce.23427

Development of novel method for quantitative determination of carbon chemical reactivity

2018· article· en· W2904344060 on OpenAlexaffvenue
Xianai Huang, Ka Wing Ng, Louis Giroux

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsThermogravimetric analysisRepeatabilityProcess engineeringCokeReactivity (psychology)Materials scienceBiological systemAnalytical Chemistry (journal)ChemistryEnvironmental chemistryEngineeringChromatographyMetallurgyOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The coke reactivity index (CRI) measurement determined with the ASTM standard is affected by both the chemical and physical properties of the coke. The contribution made by each of these factors to the measurement result cannot be easily distinguished and quantified. A new thermogravimetric analysis (TGA) technique was developed to provide further information about the chemical behaviour of the coke to facilitate an improved interpretation of the CRI measurement. The development of the technique takes into consideration the potential change in reaction rate controlling mechanism in TGA equipment. It makes use of the shrinking core model to identify the reaction rate control regime and to extract reaction rate parameters from experimental measurement. A rigorous data processing procedure was developed to ensure consistent interpretation of the measurement data while repeatability was established through measurement repetition. The sensitivity of common variable factors between different TGA apparatus on measurement results was also examined. It was demonstrated that the measurement results of this new technique are highly repeatable and reproducible.

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)0.002
metaresearch head score (Gemma)0.002
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: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.022
GPT teacher head0.251
Teacher spread0.229 · 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
GenreMethods

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

Citations1
Published2018
Admission routes2
Has abstractyes

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