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Record W7126684154

Propuesta de implementación de un Sistema Just-In-Time (JIT) en el proceso de Almacenamiento en Frío para Mejorar la Eficiencia y Calidad en una Empacadora de Camarones

2025· dissertation· es· W7126684154 on OpenAlex
Jonathan Luis Quijije Alvear

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueUniversidad Politécnica Salesiana Repositorio Digital (Universidad Politécnica Salesiana) · 2025
Typedissertation
Languagees
FieldAgricultural and Biological Sciences
TopicFood Supply Chain Traceability
Canadian institutionsnot available
Fundersnot available
KeywordsWork (physics)Turning pointQuarter (Canadian coin)
DOInot available

Abstract

fetched live from OpenAlex

En el almacenamiento en frío de camarones, los tiempos de espera afectan la calidad, frescura y textura del producto, además de aumentar los costos operativos. Este proyecto propone implementar un sistema Just-In-Time (JIT) en el área IQF antes del almacenamiento, analizando procesos actuales y eliminando cuellos de botella mediante herramientas como el ciclo de Deming. Se busca mejorar la eficiencia operativa, reduciendo tiempos de espera en un 30%, tiempos muertos en un 25% y la tasa de productos rechazados en un 20%. Además, se implementará un control de calidad en temperatura para garantizar condiciones óptimas, aplicando técnicas de mejora continua en la industria acuícola.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.122
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.004
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0060.001
Research integrity0.0040.003
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 head0.008
GPT teacher head0.273
Teacher spread0.265 · 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