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Record W2800976884 · doi:10.1002/cjce.23231

Biomass‐gas‐and‐nuclear‐to‐liquids (BGNTL) processes part I: Model development and simulation

2018· article· en· W2800976884 on OpenAlex
James A. Scott, Thomas A. Adams

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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2018
Typearticle
Languageen
FieldChemical Engineering
TopicCatalysts for Methane Reforming
Canadian institutionsMcMaster University
FundersAtomic Energy of Canada LimitedNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Research, Innovation and Science
KeywordsBiomass (ecology)Process engineeringDimethyl etherProcess (computing)Process simulationNatural gasElectricityElectricity generationEnvironmental scienceMethanolFischer–Tropsch processWaste managementNuclear engineeringEngineeringComputer scienceChemistryPower (physics)ThermodynamicsOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

Abstract New polygeneration processes for the co‐production of liquid fuels (Fischer‐Tropsch liquids, methanol, and dimethyl ether) and electricity are presented. The processes use a combination of biomass, natural gas, and nuclear energy as primary energy feeds. Chemical process models were created and used to simulate candidate versions of the process, using combinations of models ranging from complex multi‐scale models to standard process flowsheet models. The simulation results are presented for an Ontario, Canada case study to obtain key metrics such as efficiency and product conversions. Sample Aspen Plus files are provided in the supplementary material to be used by others.

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)0.001
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 score0.281
Threshold uncertainty score0.513

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.015
GPT teacher head0.217
Teacher spread0.202 · 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