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Record W2570650401 · doi:10.1002/cjce.22772

Supercritical water oxidation of lactose

2017· article· en· W2570650401 on OpenAlexaffvenue
Leandro Ferreira‐Pinto, Celia Tavares, Thiago Leandro de Souza, Andresa Carla Feihrmann, Jane Sélia dos Reis Coimbra, Diógenes R. L. Vedoy, Lúcio Cardozo‐Filho

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicSubcritical and Supercritical Water Processes
Canadian institutionsUniversity of Alberta
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsSupercritical water oxidationLactoseSupercritical fluidChemistryEffluentNuclear chemistryOrganic chemistryEnvironmental engineeringEnvironmental science

Abstract

fetched live from OpenAlex

Abstract New data on total organic carbon (TOC) reduction and H 2 production were obtained by using supercritical water oxidation of lactose with and without oxidant agents (H 2 O 2 and t‐BHP) in a continuous Inconel 625 flow reactor. The oxidation reactions were carried out at 550 and 700 °C, 22.5 MPa, 0.025 g/g (2.5 wt%) lactose concentration, feed flow rate of 5 g · min −1 , and a total reaction time of 90 min. The average production of H 2 yielded 4.5 mol/mol lactose with TOC reduction of ∼99 %. The results obtained in this study with supercritical water oxidation (SCWO) may be used to generate energy via production of H 2 from dairy industry effluents.

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 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 score0.002
Threshold uncertainty score0.270

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 head0.011
GPT teacher head0.195
Teacher spread0.184 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations7
Published2017
Admission routes2
Has abstractyes

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