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Record W4389127374 · doi:10.5151/2594-5327-15192

APLICAÇÃO PRÁTICA DE REDES NEURAIS ARTIFICIAIS NO DESENVOLVIMENTO E ADEQUAÇÃO DE AÇOS LAMINADOS A QUENTE NA USIMINAS CUBATÃO

2009· article· pt· W4389127374 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueABM Proceedings · 2009
Typearticle
Languagept
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsHumanitiesPhysicsPhilosophy

Abstract

fetched live from OpenAlex

PDF | A Assistência Técnica e o Controle Integrado da USIMINAS Cubatão têm estudado e analisado as características microestruturais e mecânicas dos aços que a empresa produz e criado modelos fenomenológicos para descrever suas propriedades. Recentemente, foi incorporada uma importante ferramenta: as Redes Neurais Adaptativas (RNA’s). Este trabalho apresenta como as RNA’s estão melhorando as atividades de desenvolvimento, adequação e aplicação de produtos laminados a quente. A composição química, temperaturas de laminação, dimensão do produto final e posição de amostragem são os parâmetros utilizados na análise das RNA’s, o que torna possível selecionar de forma efetiva e prática, e não apenas teoricamente, as melhores combinações destes parâmetros para obter um produto mais adequado.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.959
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.016
GPT teacher head0.249
Teacher spread0.233 · 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