Evidence map›Paper›PMID 40469071›Full record

ArticleFrontiers in artificial intelligence2025

Management of scientific and ancestral knowledge: a decision-making model in mezcal industry in Mexico.

Antonia Terán-Bustamante, Antonieta Martínez-Velasco, Sandra Nelly Leyva-Hernández

Abstract read
In one paragraph

Article in Frontiers in artificial intelligence, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Antonia Terán-BustamanteUniversidad Panamericana, Facultad de Ciencias Económicas y Empresariales, Ciudad de México, Mexico.
Antonieta Martínez-VelascoFacultad de Ingeniería, Universidad Panamericana, Ciudad de México, Mexico.
Sandra Nelly Leyva-HernándezTecnológico Nacional de México, Instituto Tecnológico del Valle de Etla, Oaxaca, Mexico.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Knowledge management is essential to ensure the sustainability of rural communities and small producers since it generates value for innovation, productivity, and competitiveness. The aim of this study is to identify relevant factors for adequate decision-making in managing knowledge in the Mexican mezcal industry and its impact on developing rural communities and small producers - mezcaleros. For this purpose, a decision-making model for managing scientific and ancestral knowledge is created to support links with universities, research centers, and rural communities to accelerate innovation and competitiveness in this sector. Methods: The analysis methods were carried out through decision-making, machine-learning techniques, and fuzzy logic. Results: The Bayesian Network model suggests that the preceding variables to optimize the Mezcaleros Knowledge Management are the Mezcaleros Indigenous community, the Denomination of Origin, Scientific and Ancestral Knowledge, Waste Management and Use, and Discussion: This knowledge management model aims to guide small producers to be more productive and competitive through the support of a facilitator.

Indexed as

decision-making modelfuzzy logic modelindigenous communitieslow-techmachine learningMexicoscientific and ancestral knowledgesustainability

Identifiers

PMID40469071
PMCPMC12134899

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.