MétaCan
Menu
Back to cohort
Record W1579625636 · doi:10.1590/0102-311x00126013

Assistência pré-natal no Brasil

2014· article· pt· W1579625636 on OpenAlexaboutno aff

Bibliographic record

VenueCadernos de Saúde Pública · 2014
Typearticle
Languagept
FieldHealth Professions
TopicMaternal and Neonatal Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsPrenatal careQuarter (Canadian coin)Public healthPregnancyHealth careService (business)Health professionals

Abstract

fetched live from OpenAlex

This study aims to describe prenatal care provided to pregnant users of the public or private health services in Brazil, using survey data from Birth in Brazil, research conducted from 2011 to 2012. Data was obtained through interviews with postpartum women during hospitalization and information from hand-held prenatal notes. The results show high coverage of prenatal care (98.7%), with 75.8% of women initiating prenatal care before 16 weeks of gestation and 73.1% having six or more number of appointments. Prenatal care was conducted mainly in primary health care units (89.6%), public (74.6%), by the same professional (88.4%), mostly physicians (75.6%), and 96% received their hand-held prenatal notes. A quarter of women were considered at risk of complications. Of the total respondents, only 58.7% were advised about which maternity care service to give birth, and 16.2% reported searching more than one health service for admission in labour and birth. Challenges remain for improving the quality of prenatal care, with the provision of effective procedures for reducing unfavourable 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 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)0.000
metaresearch head score (Gemma)0.003
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 score0.081
Threshold uncertainty score0.162

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.051
GPT teacher head0.382
Teacher spread0.331 · 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

Citations280
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueCadernos de Saúde PúblicaSame topicMaternal and Neonatal HealthcareFrench-language works237,207