Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The environmental health of children is one of the great global health concerns. Exposures in utero and throughout development can have major consequences on later health. However, environmental risks or disease burdens vary from region to region. Birth cohort studies are ideal for investigating different environmental risks. METHODS: The principal investigators of three birth cohorts in Asia including the Taiwan Birth Panel Study (TBPS), the Mothers and Children's Environmental Health Study (MOCEH), and the Hokkaido Study on Environment and Children' Health (Hokkaido Study) coestablished the Birth Cohort Consortium of Asia (BiCCA) in 2011. Through a series of five PI meetings, the enrolment criteria, aim of the consortium, and a first-phase inventory were confirmed. RESULTS: To date, 23 birth cohorts have been established in 10 Asian countries, consisting of approximately 70,000 study subjects in the BiCCA. This article provides the study framework, environmental exposure and health outcome assessments, as well as maternal and infant characteristics of the participating cohorts. CONCLUSIONS: The BiCCA provides a unique and reliable source of birth cohort information in Asian countries. Further scientific cooperation is ongoing to identify specific regional environmental threats and improve the health of children in Asia.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it