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Record W4365457094 · doi:10.18294/sc.2023.4325

Casamiento infantil y salud perinatal en Ecuador, 2015-2020

2023· article· es· W4365457094 on OpenAlexafffund
Dorian Ospina Galeano, Fadya Orozco, Marcelo L. Urquía

Bibliographic record

VenueSalud Colectiva · 2023
Typearticle
Languagees
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsUniversity of ManitobaManitoba Health
FundersCanadian Institutes of Health Research
KeywordsPolitical scienceMedicineGeography

Abstract

fetched live from OpenAlex

This study sought to estimate the prevalence and distribution of newborns to mothers under age 18 in Ecuador and the association between perinatal indicators and maternal marital status. Newborn records obtained from Ecuador's Instituto Nacional de Estadísticas y Censos (INEC) between 2015 and 2020 were used to assess the joint association between maternal age groups (10-15, 16-17, 18-19, and 20-24 years) and marital status (married, common-law, and single) with low birthweight, preterm birth, and inadequate prenatal care. The prevalence of newborns to mothers under age 18 was 9.3% overall, but declined over the study period, drastically among married mothers. The association between marital status and perinatal indicators depended on maternal age. The more favorable outcomes observed among married mothers aged 20-24 years (compared to their single counterparts) weaken or disappear among mothers under age 18. Mothers in stable unions exhibited outcomes in between those of married and single mothers.

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)0.001
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 score0.035
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.305
Teacher spread0.296 · 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

Citations1
Published2023
Admission routes2
Has abstractyes

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