MétaCan
Menu
Back to cohort
Record W7000389520

Feature Story: New Fulbright Canada Research Chair developing ways to better interpret comprehensive mental health assessments among children, youth, and adults

2020· other· en· W7000389520 on OpenAlexaboutno aff

Bibliographic record

VenueoURspace (University of Regina) · 2020
Typeother
Languageen
FieldEngineering
TopicManufacturing Process and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthAnxietyMoodFeature (linguistics)Data collectionMEDLINEChild healthNeeds assessment
DOInot available

Abstract

fetched live from OpenAlex

Child and youth mental health is a significant concern in Canada. According to the Canadian Institute for Health Information, an estimated 10 to 20 per cent of Canadian children and youth may develop a mental disorder. More than nine per cent of youth living in British Columbia, Saskatchewan and Manitoba are dispensed at least one medication intended to treat a mood or anxiety disorder. Yet, there are many discrepancies in how diagnostic data and treatment assessments are interpreted.

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)0.008
metaresearch head score (Gemma)0.015
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: Other · Consensus signal: none
Teacher disagreement score0.308
Threshold uncertainty score0.620

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0080.004
Scholarly communication0.0120.004
Open science0.0030.003
Research integrity0.0130.012
Insufficient payload (model declined to judge)0.1460.064

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 head0.015
GPT teacher head0.223
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

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
GenreOther

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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueoURspace (University of Regina)Same topicManufacturing Process and OptimizationFrench-language works237,207