RPS Brazilian Birth Cohorts Consortium (Ribeirão Preto, Pelotas and São Luís): history, objectives and methods
Bibliographic record
Abstract
This paper describes the history, objectives and methods used by the nine Brazilian cohorts of the RPS Brazilian Birth Cohorts Consortium (Ribeirão Preto, Pelotas and São Luís) Common thematic axes are identified and the objectives, baseline periods, follow-up stages and representativity of the population studied are presented. The Consortium includes three birth cohorts from Ribeirão Preto, São Paulo State (1978/1979, 1994 and 2010), four from Pelotas, Rio Grande do Sul State (1982, 1993, 2004 and 2015), and two from São Luís, Maranhão State (1997 and 2010). The cohorts cover three regions of Brazil, from three distinct states, with marked socioeconomic, cultural and infrastructure differences. The cohorts were started at birth, except for the most recent one in each municipality, where mothers were recruited during pregnancy. The instruments for data collection have been refined in order to approach different exposures during the early phases of life and their long-term influence on the health-disease process. The investigators of the nine cohorts carried out perinatal studies and later studied human capital, mental health, nutrition and precursor signs of noncommunicable diseases. A total of 17,636 liveborns were recruited in Ribeirão Preto, 19,669 in Pelotas, and 7,659 in São Luís. In the studies starting during pregnancy, 1,400 pregnant women were interviewed in Ribeirão Preto, 3,199 in Pelotas, and 1,447 in São Luís. Different strategies were employed to reduce losses to follow-up. This research network allows the analysis of the incidence of diseases and the establishment of possible causal relations that might explain the health outcomes of these populations in order to contribute to the development of governmental actions and health policies more consistent with reality.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.022 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".