MétaCan
Menu
Back to cohort
Record W3154657617 · doi:10.1089/can.2020.0144

Evolving Global Perspectives of Pharmacists: Dispensing Medical Cannabis

2021· review· en· W3154657617 on OpenAlexaboutno aff
Holly B. Shulman, Vashti Sewpersaud, Celeste Thirlwell

Bibliographic record

VenueCannabis and Cannabinoid Research · 2021
Typereview
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsnot available
Fundersnot available
KeywordsCannabisMedical cannabisPharmacyPharmacistPerspective (graphical)Variety (cybernetics)MedicineFamily medicineMedical educationPsychiatry

Abstract

fetched live from OpenAlex

Introduction: Different countries have employed a variety of methods for their populace to access medical cannabis. Objectives: The purpose of this literature review was to assess the international literature on pharmacists' beliefs and attitudes towards medical cannabis. Methodology: This literature review summarized the various countries that utilize pharmacies and pharmacists to dispense medical cannabis. The countries included in this review were: Australia, Canada, Denmark, Finland, Germany, Israel, Italy, Netherlands, Poland, Serbia, Switzerland, USA, and Uruguay. Discussion: The pharmacist perspective has been of key importance within the medical landscape, as they are the ones who not only dispense medication but also counsel and monitor patients and it is this perspective that is lacking. Conclusion: Overall, this review found that even though pharmacists are generally comfortable with dispensing medical cannabis; they still require further education to do so as safely and effectively as possible.

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)0.005
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.072
GPT teacher head0.450
Teacher spread0.378 · 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
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

Citations15
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueCannabis and Cannabinoid ResearchSame topicCannabis and Cannabinoid ResearchFrench-language works237,207