Optimizing pediatric clinical care and advocacy in an online era: report of the Canadian Paediatric Society Infectious Diseases and Immunization Committee.
Bibliographic record
Abstract
OBJECTIVE: To help busy FPs find useful current information and keep up to date on pediatric infectious disease and immunization topics by highlighting the work of one excellent source of reliable information in this area, the Canadian Paediatric Society Infectious Diseases and Immunization Committee. COMPOSITION OF THE COMMITTEE: Committee members were appointed to represent the Canadian Paediatric Society, the College of Family Physicians of Canada, the Public Health Agency of Canada, the American Academy of Pediatrics, and the National Advisory Committee on Immunization. METHODS: This article highlights important pediatric practice points generated by the Canadian Paediatric Society Infectious Diseases and Immunization Committee at a typical meeting in January 2013 from the perspective of an FP liaison. It also describes the committee's work methods and its background thinking related to the most current and changing issues. REPORT: Learn specific online links to updated pediatric infectious disease topics from the detailed content of this report. Topics include caring for kids new to Canada, vaccine-hesitant parents, influenza, human papillomavirus, pertussis, sexually transmitted infections, multidrug-resistant bacteria, and advocacy, among others. CONCLUSION: Learn where to find this new and continuously changing information and how to stay evergreen in your knowledge.
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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 | 0.024 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.006 | 0.006 |
| 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".