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Record W3011156829 · doi:10.5770/cgj.23.424

Canadian Guidelines on Cannabis Use Disorder Among Older Adults

2020· article· en· W3011156829 on OpenAlexafffundvenueabout
Jonathan Bertram, Amy Porath, Dallas Seitz, H. Kalant, Ashok Krishnamoorthy, Andra Smith, Rand Teed

Bibliographic record

VenueCanadian Geriatrics Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsMcMaster UniversityUniversity of OttawaUniversity of British ColumbiaBruyèreCentre for Addiction and Mental HealthVancouver Coastal HealthUniversity of CalgaryCanadian Centre on Substance Use and AddictionHamilton Health SciencesUniversity of Toronto
FundersHealth Canada
KeywordsMedicineCannabisPsychiatryMental healthSubstance useGerontology

Abstract

fetched live from OpenAlex

BACKGROUND: Cannabis Use Disorder (CUD) is an emerging and diverse challenge among older adults. METHODS: The Canadian Coalition for Seniors' Mental Health, with financial support from Health Canada, has produced evidence-based guidelines on the prevention, identification, assessment, and treatment of this form of substance use disorder. CONCLUSIONS: Older adults may develop CUD in the setting of recreational and even medical use. Clinicians should remain vigilant for the detection of CUD, and they should be aware of strategies for prevention and managing its emergence and consequences The full version of these guidelines can be accessed at www.ccsmh.ca.

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)0.006
metaresearch head score (Gemma)0.027
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 score0.105
Threshold uncertainty score0.212

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0080.007
Science and technology studies0.0040.002
Scholarly communication0.0020.002
Open science0.0050.002
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0230.009

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 head0.024
GPT teacher head0.279
Teacher spread0.254 · 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

Citations35
Published2020
Admission routes4
Has abstractyes

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Same venueCanadian Geriatrics JournalSame topicCannabis and Cannabinoid ResearchFrench-language works237,207