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Design of Pilot Scale for Measuring the Security of Access to Water in Guanajuato, Mexico

2015· article· en· W1584815713 on OpenAlexaff
Rebeca Monroy‐Torres, Jaime Naves‐Sánchez, Hugo Melgar‐Quiñonez

Bibliographic record

VenueThe FASEB Journal · 2015
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsMcGill University
Fundersnot available
KeywordsFood securityWater securityScale (ratio)BusinessEnvironmental scienceEnvironmental economicsEnvironmental resource managementGeographyWater resourcesAgricultureEcologyEconomicsBiology

Abstract

fetched live from OpenAlex

Introduction Food security is the state in which all persons have always access to the food needed to meet their dietary requirements, but food security cannot be achieved without considering the access to water (water security – WS). Considered a human right, water must meet the following criteria: sufficient, safe, acceptable, available, and accessible (FAO, 2002). Objective To identify the state of food security and access to water in Mexican households. Methods Water security was assessed using a pilot scale. The scale was applied as part of a survey in 458 households, containing also an experience‐based food security scale ( Escala Latinoamericana y Caribeña de Seguridad Alimentaria). Results The water security scale contains 17 items addressing four domains concerning water: one for sufficiency, six for safety, one for acceptability, four for availability and five for access, concerning costs and physical access (FAO, 2002). Conclusions Water Security is a human right, internationally recognized. The proposed scale represents an instrument that allows assessing issues related to the lack of appropriate access to water.

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)0.005
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.116
GPT teacher head0.315
Teacher spread0.199 · 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 designObservational
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
Published2015
Admission routes1
Has abstractyes

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