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Record W2053803763 · doi:10.1016/j.eurpsy.2008.01.1302

The place of the Western Canada waitlist project in regional child and adolescent mental health program services

2008· article· en· W2053803763 on OpenAlexaffabout
David Cawthorpe, T. Christopher Wilkes, Kwame McKenzie, Cho Hun Ha

Bibliographic record

VenueEuropean Psychiatry · 2008
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsAlberta Health Services
Fundersnot available
KeywordsMental healthTriageIntervention (counseling)Presentation (obstetrics)MedicinePsychologyNursingPsychiatry

Abstract

fetched live from OpenAlex

The Place of the Western Canada Waitlist Project in Regional Child and Adolescent Mental Health Program Services.In this presentation is described the history of the Western Canada Waitlist Project (WCWL) and its implementation within the Child and Adolescent Mental Health Program. Highlighted is how the Western Canada Waitlist Project fits into regional clinical and accountability processes. Our results confirm that the Western Canada Waitlist Project Children's Mental Health component is a useful, economic instrument. For example, 11,067 Children's Mental Health Priority Criteria Score (CMH-PCS) forms have been completed since the beginning of the project in 2002. Not only have the WCWL data been used clinically to place clients within the continuum of care and develop priority and safety flags, the WCWL data have also been used to predict and model clinical outcomes. The current paper highlights the degree to which the WCWL-CMH-PCS, gathered at the time of screening and triage, prior to admission, predicts clinical outcomes at the time of discharge. Described is the way in which we plan to use this information to flag on admission, for the purpose of additional intervention, children who are at risk of poor clinical outcomes.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.317

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.003
Scholarly communication0.0040.001
Open science0.0020.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.001

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 head0.014
GPT teacher head0.258
Teacher spread0.244 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations1
Published2008
Admission routes2
Has abstractyes

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