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Record W2588366537 · doi:10.3895/recit.v7.n15.4349

Heurística de Teitz e Bart na resolução de um problema logístico

2016· article· pt· W2588366537 on OpenAlexaff
Eduardo Gasparin, Levi Lopes Teixeira

Bibliographic record

VenueRevista Eletrônica Científica Inovação e Tecnologia · 2016
Typearticle
Languagept
FieldDecision Sciences
TopicBusiness and Management Studies
Canadian institutionsMinistry of Transportation of Ontario
Fundersnot available
KeywordsPhysicsPhilosophy

Abstract

fetched live from OpenAlex

O objetivo deste trabalho foi definir um número limitado de cidades nas quais uma empresa de logística no estado do Paraná esta instalando seus centros de distribuição. A partir do levantamento bibliográfico o problema foi definido e encontrado um método adequado para sua solução. Com as informações pertinentes as cidades atendidas, foi possível baseado na heurística de Teitz e Bart, definir quais seriam contempladas com a instalações dos centros de distribuição, de forma que minimizasse os custos de transporte para a empresa mencionada.

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)0.008
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.883
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.004
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0040.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.004

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 head0.077
GPT teacher head0.339
Teacher spread0.262 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2016
Admission routes1
Has abstractyes

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