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Record W1503999499 · doi:10.22409/engevista.v11i2.235

MODELAGEM DE PROBLEMAS DE REAÇÃO EM CATALISADORES POROSOS SUJEITOS À LIMITAÇÃO DIFUSIONAL INTERNA DE CALOR E MASSA UTILIZANDO UM AMBIENTE COMPUTACIONAL INTERATIVO DESENVOLVIDO EM MAPLE

2010· article· pt· W1503999499 on OpenAlexaff
Fabiana Vassallo Caldas, Rosenir Rita de Cássia Moreira da Silva, Arlindo de Almeida Rocha

Bibliographic record

VenueEngevista · 2010
Typearticle
Languagept
FieldEngineering
TopicCatalysis for Biomass Conversion
Canadian institutionsPetro-Canada
Fundersnot available
KeywordsPhysicsMapleHumanitiesPhilosophyBiology

Abstract

fetched live from OpenAlex

Este trabalho apresenta a aplicação de um software de matemática o “MAPLE” como um meio didático para cálculos complexos especialmente relacionados às reações catalíticas que ocorrem em catalisadores porosos, com diversas geometrias, sujeitos às limitações difusionais internas à transferência de massa e calor, simultaneamente. O problema foi formulado a partir das equações gerais da conservação de massa e energia, utilizando uma rotina desenvolvida para o Software MAPLE, particularizado e solucionado numericamente. Calculou-se o fator de efetividade em função do módulo de Thiele para grãos esféricos, cilíndricos e em forma de placa plana, devido à característica interativa do ambiente desenvolvido. Foram obtidos também os perfi s adimensionais de concentração e de temperatura no interior de um grão esférico para reações exotérmicas e endotérmicas.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.242
Teacher spread0.228 · 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 designSimulation or modeling
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

Citations1
Published2010
Admission routes1
Has abstractyes

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