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Record W3198687654 · doi:10.51731/cjht.2021.127

Medications Containing Low-Dose Codeine for the Treatment of Pain and Coughs

2021· article· en· W3198687654 on OpenAlexaboutno aff
Calvin Young, Hannah Loshak

Bibliographic record

VenueCanadian Journal of Health Technologies · 2021
Typearticle
Languageen
FieldMedicine
TopicRespiratory and Cough-Related Research
Canadian institutionsnot available
Fundersnot available
KeywordsCodeineMedicineMedical prescriptionMorphineNarcoticPharmacologyAnesthesia

Abstract

fetched live from OpenAlex


 Codeine and codeine-containing medicines are used to treat people experiencing pain or cough symptoms. Whereas most products containing codeine require a prescription in Canada, some jurisdictions permit over-the-counter sales of products containing low doses of codeine mixed with other non-narcotic medicinal ingredients.
 Three overviews of reviews and 13 systematic reviews of variable methodological quality failed to identify studies on the effectiveness of low-dose codeine (i.e., 8 mg of codeine per tablet or 20 mg of codeine per 30 mL in liquid products) for the treatment of pain or coughs.
 There is a lack of evidence on the clinical effectiveness of oral analgesics and oral antitussives containing low doses of codeine.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.991
Threshold uncertainty score0.786

Codex and Gemma teacher scores by category

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

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 head0.056
GPT teacher head0.353
Teacher spread0.297 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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

Citations1
Published2021
Admission routes1
Has abstractyes

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