Bibliographic record
Abstract
o give the best care to patients and families, paediatricians need to integrate the highest quality scientific evidence with clinical expertise and the opinions of the family. 1 Archimedes seeks to assist practising clinicians by providing ''evidence-based'' answers to common questions that are not at the forefront of research but are at the core of practice.In doing this, we are adapting a format that has been successfully developed by Kevin Mackway-Jones and the group at the Emergency Medicine Journal-''BestBets''.A word of warning.The topic summaries are not systematic reviews, although they are as exhaustive as a practising clinician can produce.They make no attempt to statistically aggregate the data, nor to search the grey, unpublished literature.What Archimedes offers is practical, best evidencebased answers to practical, clinical questions.The format of Archimedes may be familiar.A description of the clinical setting is followed by a structured clinical question.(These aid in focusing the mind, assisting searching 2 and obtaining answers.3 ) A brief report of the search used follows-this has been performed in a hierarchical way, to search for the best quality evidence to answer the question (http://www.cebm.net).A table provides a summary of the evidence and key points of the critical appraisal.For further information on critical appraisal, and the measures of effect (such as the number needed to treat), books by Sackett 4 and Moyer 5 may help.To pull the information together, a commentary is provided, but to make it all much more accessible, a box provides the clinical bottom lines.Electronics-only topics that have been published on the BestBets site (www.bestbets.org)and may be of interest to paediatricians include the following. N Can steroids be used to reduce post tonsillectomy pain?Readers wishing to submit their own questions-with best evidence answers-are encouraged to review those already proposed at www.bestbets.org.If your question still hasn't been answered, feel free to submit your summary according to the instructions for authors at www.archdischild.com.Three topics are covered in this issue of the journal:N Is teething the cause of minor ailments?N Should steroid creams be used in cases of labial fusion?N Does erythromycin cause pyloric stenosis?
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.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".