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Record W2126767763

Alternating acetaminophen and ibuprofen for pain in children.

2012· article· en· W2126767763 on OpenAlexaff
Christine H. Smith, Ran D. Goldman

Bibliographic record

VenuePubMed · 2012
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsBC Children's Hospital
Fundersnot available
KeywordsIbuprofenAcetaminophenMedicineRegimenOver-the-counterAnesthesiaPhysical therapySurgeryPharmacologyMedical prescription
DOInot available

Abstract

fetched live from OpenAlex

QUESTION: Because pain is a very common condition in children, such as after musculoskeletal injuries, many parents ask whether they can alternate over-the-counter analgesics to treat their children's pain. While some guidelines advise against this, it is common practice. Should alternating acetaminophen and ibuprofen be recommended for treating pain in children? ANSWER: Children who have unresolved pain despite the use of either ibuprofen or acetaminophen should have their medication regimen reviewed to ensure they are receiving the medication at an adequate dose and interval. If monotherapy has failed, a short trial of an alternating regimen could be implemented. However, there is a lack of evidence for safety with long-term use of alternating ibuprofen and acetaminophen.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.027
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0050.002
Insufficient payload (model declined to judge)0.0270.009

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.

Opus teacher head0.022
GPT teacher head0.238
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations16
Published2012
Admission routes1
Has abstractyes

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