2020 edition of the Rourke Baby Record
Bibliographic record
Abstract
OBJECTIVE: To update primary care providers practising well-child and well-baby clinical care on the evidence that contributed to the recommendations of the 2020 edition of the Rourke Baby Record (RBR). QUALITY OF EVIDENCE: Pediatric preventive care literature was searched from June 2016 to May 2019, primary research studies were reviewed and critically appraised using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) methodology, and recommendations were updated where there was support from the literature. MAIN MESSAGE: Notable changes in the 2020 edition of the RBR include the recommendations to limit or avoid consumption of highly processed foods high in dietary sodium, to ensure safe sleep (healthy infants should sleep on their backs and on a firm surface for every sleep, and should sleep in a crib, cradle, or bassinette in the parents' room for the first 6 months of life), to not swaddle infants after they attempt to roll, to inquire about food insecurity, to encourage parents to read and sing to infants and children, to limit screen time for children younger than 2 years of age (although it is accepted for videocalling), to educate parents on risks and harms associated with e-cigarettes and cannabis, to avoid pesticide use, to wash all fruits and vegetables that cannot be peeled, to be aware of the new Canadian Caries Risk Assessment Tool, to note new red flags for cerebral palsy and neurodevelopmental problems, and to pay attention to updated high-risk groups for lead and anemia screening. CONCLUSION: The RBR endeavours to guide clinicians in providing evidence-informed primary care to Canadian children. The revisions are rigorously considered and are based on appraisal of a growing, albeit still limited, evidence base for pediatric preventive care.
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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 | 0.027 | 0.174 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.071 | 0.051 |
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".