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Record W3200910228 · doi:10.1097/cxa.0000000000000122

Concurrent Disorders Management in Psychiatric Care: Opportunities and Challenges

2021· article· en· W3200910228 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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueThe Canadian Journal of Addiction · 2021
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsCentre for Addiction and Mental HealthUniversity of CalgaryUniversity of British ColumbiaOntario Shores Centre for Mental Health SciencesBritish Columbia Centre on Substance UseUniversity of Toronto
Fundersnot available
KeywordsPsychiatryAddictionSubstance useMedicineSubstance abuseEpidemiology of child psychiatric disordersPsychology

Abstract

fetched live from OpenAlex

Despite increased awareness of the prevalence and burden of substance use disorders, there is limited access to addiction treatment services in Canada, including in psychiatric settings. While substance use disorders are highly comorbid and confer a poorer prognosis on psychiatric illnesses, psychiatric services are often ill-equipped in managing comorbid addictions. While there has slowly been an increase in recognition of this deficit in psychiatric training, there continues to be a deficit in concurrent disorder services in psychiatric care. A potential strategy to address this gap in clinical services is a concurrent disorder consult model. Herein, we outline a model for improved access to addiction treatment in psychiatric care and outline considerations for developing concurrent disorder consult services.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical
Teacher disagreement score0.895
Threshold uncertainty score0.848

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.050
GPT teacher head0.258
Teacher spread0.208 · 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