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Record W6944098013 · doi:10.17605/osf.io/urj4b

Interventions to address potentially inappropriate prescriptions and over-the-counter medication use among older adults: An evidence synthesis to inform the Canadian Task Force on Preventive Health Care

2021· article· en· W6944098013 on OpenAlexaboutno aff

Bibliographic record

VenueOSF Preprints (OSF Preprints) · 2021
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedical prescriptionPsychological interventionHealth careTask forceMEDLINEPublic healthAlternative medicineTask (project management)

Abstract

fetched live from OpenAlex

To inform recommendations by the Canadian Task Force on Preventive Health Care on potentially inappropriate prescriptions and over-the-counter (OTC) medication use among adults aged 65 years and older in relevant primary care settings. The evidence synthesis will review the 1) benefits and harms and 2) acceptability of interventions to reduce potentially inappropriate prescriptions and over-the-counter medication use. Key question 1: What are the benefits and harms of interventions to reduce potentially inappropriate prescriptions and over-the-counter medication use in adults aged 65 and older? Key question 2: What is the acceptability of interventions to address potentially inappropriate prescriptions and over-the-counter medication use in adults aged 65 and older?

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)0.038
metaresearch head score (Gemma)0.170
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.981
Threshold uncertainty score0.426

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0380.170
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.009
Bibliometrics0.0060.006
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0070.001

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 head0.052
GPT teacher head0.365
Teacher spread0.313 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations0
Published2021
Admission routes1
Has abstractyes

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