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Record W2785847215 · doi:10.30930/ig.8.2

Plan de muestreo de tres clases Caso de mejora en inspección de materia prima con base en curvas características de operación en una industria de alimentos

2018· article· es· W2785847215 on OpenAlexaff
Mairett Rodríguez-Balza, Luis Pérez-Ybarra, Mayorly Tatiana González Bueno

Bibliographic record

VenueInnotec gestión · 2018
Typearticle
Languagees
FieldComputer Science
TopicExperience-Based Knowledge Management
Canadian institutionsKellogg's (Canada)
Fundersnot available
KeywordsHumanitiesPhysicsMathematicsArt

Abstract

fetched live from OpenAlex

l plan de muestreo por aceptación de materia prima para la elaboración de la naranjada al 60 %, aplicado por una empresa venezolana de alimentos, consiste en un muestreo de tres clases en el cual se seleccionan al azar n=5 bidones de concentrado de naranja de aproximadamente N=8 o 10 bidones en promedio, y en caso de presentarse más de c=2 bidones con carga microbiana considerada como marginalmente aceptable, el lote de materia prima es rechazado.En este trabajo se analizó el comportamiento de varios planes de muestreo alter- INNOTEC Gestión, 2017,

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.026
GPT teacher head0.305
Teacher spread0.278 · 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
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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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