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Record W7133043542

Propuesta para incrementar las ventas de la crema de maní de manitoba a traves de la creación de un adobo

2024· dissertation· es· W7133043542 on OpenAlexaboutno aff
Carolina Oviedo Rivera, Ada Valery Escobar Parra, Luis Alexander Moreno Raigosa

Bibliographic record

VenueBiblioteca Digital - Universidad Icesi · 2024
Typedissertation
Languagees
FieldEconomics, Econometrics and Finance
TopicBusiness, Innovation, and Economy
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityProduct (mathematics)Consumption (sociology)IngredientFood productsProduct lineSustainable development
DOInot available

Abstract

fetched live from OpenAlex

This proposal details a strategy to increase the use of peanut butter through a marinade, focusing on the development of a new product line called MANIDOBO from the company MANITOBA . The objective is to create a peanut butter - based 2 product that responds to the growing consumer demand for healthy and sustainable options, becoming an essential ingredient in Colombian gastronomy. Global market trends indicate a steady increase in the consumption of marinades that are low in sodium, free of preservatives and made with natural ingredients, reflecting a preference for healthier alternatives, driven by increased awareness about food an d demand for sustainable products. Market research, based on a survey, shows that a high percentage of participants are interested in trying traditional dishes that include peanut marinade. This, together with data from secondary sources, highlights the fe asibility of introducing innovative products in this sector, allowing the implementation of effective strategies in digital marketing, sustainability and product development.

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)0.002
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: Other · Consensus signal: none
Teacher disagreement score0.788
Threshold uncertainty score0.422

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.002

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 head0.015
GPT teacher head0.240
Teacher spread0.225 · 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
GenreOther

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
Published2024
Admission routes1
Has abstractyes

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