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Record W2329643959 · doi:10.4081/jphia.2015.357

Use of pulse crops in complementary feeding of 6-23-month-old infants and young children in Taba Kebele, Damot Gale District, Southern Ethiopia

2016· article· en· W2329643959 on OpenAlexafffund
Addisalem Mesfin, Carol J. Henry, Meron Girma, Susan J. Whiting

Bibliographic record

VenueJournal of Public Health in Africa · 2016
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsUniversity of Saskatchewan
FundersGlobal Affairs CanadaInternational Development Research Centre
KeywordsDietary diversityFood groupMalnutritionMicronutrientEnvironmental healthFocus groupMedicineFood securityAgriculturePediatricsBiologyEcology

Abstract

fetched live from OpenAlex

Poor complementary feeding practices contribute to infants and young children (IYC) malnutrition, with lack of protein-containing food and micronutrients as major concerns. A cross-sectional survey was conducted to assess the dietary diversity, nutrient contents and use of pulse crops in complementary feeding at Taba kebele, Southern Ethiopia. A questionnaire was used to collect socio-demographic and dietary diversity data from a random sample of 128 mother-child pairs. A one day weighed food record assessed IYC median nutrient intake. Focus group discussion explored mothers' perceptions and use of pulse crops in complementary food preparation. Dietary diversity assessment found that 43.7% consumed pulses, and only 18.7% consumed meat and 26.6% eggs. Focus group discussion showed that mothers had little interest in incorporating pulses into complementary foods. Raising awareness of mothers/caregivers on food diversification and promoting the inclusion of pulses in food preparation for infants and young children are vital to nutritional status of IYC.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.021
Threshold uncertainty score0.746

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.066
GPT teacher head0.312
Teacher spread0.246 · 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.

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

Citations17
Published2016
Admission routes2
Has abstractyes

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