MétaCan
Menu
Back to cohort

Unconditional Prenatal Income Supplement and Birth Outcomes

2016· article· en· W2531238086 on OpenAlexaff
Marni Brownell, Mariette Chartier, Nathan Nickel, Dan Château, Patricia J. Martens, Joykrishna Sarkar, Elaine Burland, Douglas P. Jutte, Carole Taylor, Robert Santos, Alan Katz

Bibliographic record

VenueObstetrical & Gynecological Survey · 2016
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsManitoba Health
Fundersnot available
KeywordsMedicineLow birth weightPrenatal careEnvironmental healthBirth weightConditional cash transferPediatricsPregnancyPovertyEconomic growthPopulation

Abstract

fetched live from OpenAlex

(Abstracted from Pediatrics 2016;137(6):e20152992) The prenatal period is an important period that impacts newborn and lifelong health; exposure to stress, poor nutrition, or substance abuse during this period leads to adverse birth outcomes, including low birth weight and preterm birth. Several initiatives across the world that utilize conditional cash or food transfer include Oportunidades (Mexico), Bolsa Familia Program (Brazil), and the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC, United States) have been undertaken to improve prenatal health and birth outcomes.

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)0.001
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.044
GPT teacher head0.312
Teacher spread0.268 · 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 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

Citations5
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueObstetrical & Gynecological SurveySame topicBirth, Development, and HealthFrench-language works237,207