Medicines for children: A global gift of trusted accessible information for parents
Bibliographic record
Abstract
To engender safer medication practice the Government of Canada encourages families to, "Ask your doctor about your child's medication." Medicines for Children (MFC) was established in 2006 when the U.K.'s Royal College of Paediatrics and Child Health (RCPCH), Wellchild charity, and the Neonatal and Paediatric Pharmacy Group (NPPG) listened to parents' concerns that they needed better information on children's medicines. Each one of the >200 information sheets available on the website has gone through a standardized, audited development. When launched in 2009 there were 10,500 hits by 7000 unique users which has grown to 4.5 million hits from 3.6 million individuals in 2022. Although the UK has the largest number of users; its worldwide importance is demonstrated by the fact that there are 430,000 users in Canada. For parents of a child who needs to take medicines safely, MFC provides high-quality, reliable family-centred information accessible 24/7 across the globe.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.072 | 0.024 |
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".