Treatments for cough and common cold in children
Bibliographic record
Abstract
This is comment on: Gill PJ, Onakpoya IJ, Buchanan F, Birnie KA, Van den Bruel A. Treatments for cough and common cold in children. BMJ. 2024 Jan 25;384:e075306. https://pubmed.ncbi.nlm.nih.gov/38272497 Gill et al. reviewed common cold treatments for children [1]. In Table 2 they refer to our Cochrane review on vitamin C and the common cold [2] and state the summary of evidence as “No consistent effect [of vitamin C] on the duration or severity of colds”. The topic is not discussed any further in the text section. In fact, in our Cochrane review we calculated that in placebo-controlled trials, regular >0.2 g/day vitamin C shortened the duration of colds in children by 14.2% (7.3 to 21%; P = 0.00005); Analysis 2.1.2 (Trials with children) [2]. Furthermore, our calculation is based on 14 comparisons, whereas Gill states in their table that the number of vitamin C studies in our review on was 7. Thus, in contrast to Gill’s statement, our meta-analysis found that there is a consistent beneficial effect of regular vitamin C administration on common cold duration in children.
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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 | 0.009 | 0.057 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.016 | 0.020 |
| Insufficient payload (model declined to judge) | 0.035 | 0.014 |
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".