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Aprovechamiento de subproductos de Concha de Abanico (Argopecten purpuratus) para la elaboración de nuevos productos

2022· article· es· W4323345573 on OpenAlexaff
Josue Ccopa, Claudia Puelles, Wilmer Rivas, Luis La Chira

Bibliographic record

VenueCiencia Unemi · 2022
Typearticle
Languagees
FieldAgricultural and Biological Sciences
TopicBotanical Research and Applications
Canadian institutionsGrieg Seafood (Canada)
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

El objetivo de la investigación fue elaborar prototipos de productos alternativos con subproductos de Concha de Abanico (Argopecten purpuratus) cuyas características fueran de aceptación para los potenciales consumidores, con la visión de la comercialización de los mismos. Se elaboraron cuatro prototipos de conservas en líquido de gobierno (aceite de girasol, salsa de tomate, salsa de espárragos y escabeche) con dos presentaciones cada uno (con y sin vísceras), dos prototipos tipo Paté ahumado (sin y con especies) y tres pastas o preformados congelados (Nuggets, Hamburguesa, Tallos empanizados). Todos los prototipos se prepararon siguiendo los protocolos de elaboración respectivos y siguiendo las normas de higiene correspondientes. Se evaluaron todos los prototipos mediante análisis sensoriales con tres expertos y se reportaron los resultados promedio. Se obtuvo que todos los prototipos presentaron de buena a muy buena aceptabilidad y se destacó las Conchas de Abanico Ahumadas en Aceite Girasol evisceradas, sobre todo por su sabor y apariencia. La presencia de vísceras en el producto afecta la textura y produce menor aceptabilidad en comparación con los productos que no las contienen. Al igual que las conservas, las pastas o preformados congelados son productos con buenas propiedades sensoriales y que pueden ser comercializados como productos alternativos.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.793
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.286
Teacher spread0.266 · 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 teacher head, not a consensus.

Study designBench or experimental
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
Published2022
Admission routes1
Has abstractyes

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