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Record W2758439893 · doi:10.5151/1983-4764-27695

TECNOLOGIAS DO NOVO LAMINADOR DE CHAPAS GROSSAS DA GERDAU

2017· article· pt· W2758439893 on OpenAlexaff
Rafael Abreu Fraga, Rodney Pardo Alves, Flávio Viana de Freitas, Emanuelle Garcia Reis, Maurício Martins Pereira, José Herbert Dolabela da Silveira

Bibliographic record

Venuenot available
Typearticle
Languagept
FieldAgricultural and Biological Sciences
TopicAgricultural and Food Sciences
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

ResumoEm qualquer novo investimento, o desafio é ter um projeto com uma fábrica com flexibilidade para produzir uma ampla gama de produtos de alto valor agregado para atender a demandas futuras dos setores de energia, naval, construção e equipamentos pesados.O emprego de equipamentos robustos com elevado nível de automação é fundamental para isso.Um componente chave é a utilização da laminação totalmente automática através de modelos físicos integrados com o controle dos equipamentos e das temperaturas de processo objetivando alcançar patamares diferenciados de produtividade e qualidade.Este trabalho visa apresentar os novos recursos técnológicos incorporados a nova linha de Laminação de Chapas Grossas da Gerdau em Ouro Branco/MG;

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.059
GPT teacher head0.269
Teacher spread0.210 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2017
Admission routes1
Has abstractyes

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