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Record W4403319111 · doi:10.63042/t8rwm964

La aplicación de MESMIS para el impulso de la agricultura urbana yperiurbana en la construcción de territorios sustentables en el Centro deMéxico

2024· article· es· W4403319111 on OpenAlexaff
Silvia Iveth Moreno Gaytán, Héctor Ávila Sánchez

Bibliographic record

VenueRegiones y desarrollo sustentable. · 2024
Typearticle
Languagees
FieldSocial Sciences
TopicRegional Development and Innovation
Canadian institutionsComputer Research Institute of Montréal
Fundersnot available
KeywordsHumanitiesGeographyArt

Abstract

fetched live from OpenAlex

This paper is the result of the research entitled “Towards food sustainability: Urban and peri-urbanagriculture networks in Central Mexico”, whose objective is to examine the interrelationships ofrural-urban spaces in function of the sustainability of urban and peri-urban agriculture to formshort circuits for the benefit of the environment and peasant lifestyles within the agri-food systemsof the region within the framework of the project “Mega-Urbanization in the Central Region ofMexico, Socio-Territorial Inequality and New Peri-Urbanization Processes. (Project PAPIIT IG300122). The analysis approach was carried out with the Framework for the Evaluation of NaturalResource Management Systems Incorporating Sustainability Indicators (MESMIS) for two casestudies of new markets derived from agroecology brought about in the midst of the Sars Cov-2,Covid-19 pandemic. Likewise, cartographic tools were used to integrate agri-food systems. Thediscussion addresses how urban agriculture practices contribute to improving local food systems.The results identify the basket of goods offered by peri-urban territories to guide regions andfood systems towards sustainability, seeking to strengthen the preservation of social and naturalresources in the Central Region of Mexico.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.729
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.009
GPT teacher head0.312
Teacher spread0.303 · 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 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
Published2024
Admission routes1
Has abstractyes

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