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Record W3213947729 · doi:10.34117/bjdv7n10-128

Aplicação da metodologia de análise e solução de problemas (MASP) na logística de uma empresa do setor agroindustrial / Application of the analysis and problem solving methodology (MASP) in the logistics of a company in the agroindustrial sector

2021· article· pt· W3213947729 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

VenueBrazilian Journal of Development · 2021
Typearticle
Languagept
FieldDecision Sciences
TopicBusiness and Management Studies
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsComputer scienceHumanitiesPhysicsPhilosophy

Abstract

fetched live from OpenAlex

O objetivo do trabalho é aplicar o Método de Análise e Solução de Problemas (MASP) no setor logístico de uma empresa de grande porte do setor agroindustrial. A empresa comercializa insumos, máquinas e implementos agrícolas. A ideia central do estudo é analisar os problemas existentes no processo, observar e identificar as causas mais impactantes de acordo com os procedimentos da metodologia. O método utilizado para realização da coleta dos dados foi à observação direta com os colaboradores e responsáveis pelos processos da logística da empresa. Foram identificados cinco problemas na Logística e o principal foi o atraso na entrega com o maior nível de priorização. Após a identificação deste problema, as etapas do MASP foram aplicadas, visando à investigação das causas e a elaboração de um plano de ação para bloquear as causas fundamentais diagnosticadas. O MASP e as ferramentas da qualidade utilizadas podem ser destacados como aplicações úteis para melhorias de processos e foram extremamente significativas para atacar o principal problema da empresa estudada.

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)0.023
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.355
Threshold uncertainty score0.866

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0230.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
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 head0.199
GPT teacher head0.375
Teacher spread0.176 · 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