Rourke Baby Record 2017: Clinical update for preventive care of children up to 5 years of age.
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
OBJECTIVE: To describe the process and evidence used to update preventive care recommendations in the 2017 Rourke Baby Record to assist primary care providers' decisions around which maneuvers to prioritize and implement in practice. QUALITY OF EVIDENCE: A search of the literature from June 2013 to June 2016 was conducted, using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) methodology to critically appraise primary research studies, and recommendations were changed where there was substantial support from the new literature. MAIN MESSAGE: The important changes in preventive care recommendations for children up to 5 years of age include the addition of body mass index monitoring as of 2 years of age; stronger evidence to support the introduction of allergenic foods without delay (strength of recommendation change from fair to good); the recommendation to ask validated questions regarding the effects of poverty; evidence showing no safe level of lead exposure in children; the recommendation of a daily sleep duration; the upgrade of recommendation strength from fair to good of items related to the prevention and detection of adverse childhood experiences, including assessment of bruising in babies younger than 9 months; and blood pressure monitoring only for children at risk. CONCLUSION: Early childhood exposures and habits have short- and long-term health consequences. The Rourke Baby Record will continue to publish updates to ensure that primary care providers are equipped to promote lifelong health and well-being through evidence-informed care in young children.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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