MétaCan
Menu
Back to cohort
Record W2022942973 · doi:10.1080/16066350802334587

Drawing the line on risky use of cannabis: Assessing problematic use with the ASSIST

2009· article· en· W2022942973 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAddiction Research & Theory · 2009
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsGovernment of Northwest TerritoriesCentre for Drug Research and DevelopmentCanadian Centre on Substance Use and AddictionCarleton University
Fundersnot available
KeywordsCannabisAddictionSubstance usePsychologyPsychiatryMedicine

Abstract

fetched live from OpenAlex

Health and social harms from cannabis use typically are assessed by comparing those who use to those who do not use. Recognizing that not all use of cannabis is necessarily problematic, we examine rates of self-reported harms as a function of frequency of use. Second, we assess the effectiveness of the cannabis portion of the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) as a screening tool for identifying problematic cannabis users. Data come from the Canadian Addiction Survey (CAS; N = 13,909) and the 2006 NWT Addictions Survey (2006 NWTAS; N = 1235). Results from both surveys indicate that harms are most likely among weekly and daily users. Although frequent users are at increased risk of harms, greater balance of sensitivity with specificity is obtained with the ASSIST screening tool using a somewhat higher threshold than what is suggested in clinical applications of the instrument. Implications for this higher threshold for public policy are discussed.

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.

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)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.617
Threshold uncertainty score0.696

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.073
GPT teacher head0.376
Teacher spread0.303 · 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