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Record W1560051163 · doi:10.1093/pch/16.9.564

Treating cough and cold: Guidance for caregivers of children and youth

2011· article· en· W1560051163 on OpenAlexaff
Ran D. Goldman

Bibliographic record

VenuePaediatrics & Child Health · 2011
Typearticle
Languageen
FieldMedicine
TopicRespiratory and Cough-Related Research
Canadian institutionsCanadian Paediatric Society
Fundersnot available
KeywordsMedicinePsychology

Abstract

fetched live from OpenAlex

Despite the widespread use of over-the-counter (OTC) cough and cold medications (CCMs), the effectiveness of most CCMs has not been proven in children. A meta-analysis summarizing trials using OTC CCMs for viral-induced cough found no evidence for or against the use of OTC medicines in both paediatric and adult populations when cough frequency and severity, as well as physician assessments, were compared. Furthermore, North American data suggest that OTC CCMs may be associated with medication errors and adverse events, resulting in visits to emergency departments and even leading to death. The present article provides information on current evidence for cough and cold therapies, including fluid intake, humidified air, antihistamines, echinacea, zinc, honey and vitamin C, for caregivers of children and youth.

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)0.003
metaresearch head score (Gemma)0.016
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: Methods · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0020.002
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0110.003

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 head0.032
GPT teacher head0.295
Teacher spread0.263 · 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
GenreMethods

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

Citations19
Published2011
Admission routes1
Has abstractyes

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