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Record W1982192197 · doi:10.3390/challe2010001

Using a Mobile Laboratory to Study Mental Health, Addictions and Violence: A Research Plan

2011· article· en· W1982192197 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueChallenges · 2011
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsHospital for Sick ChildrenLaurentian UniversityCanada Research ChairsMcMaster UniversityUniversity of TorontoCentre for Addiction and Mental HealthWestern University
FundersCanadian Institutes of Health ResearchQueen's University
KeywordsMental healthPlan (archaeology)AddictionPovertyPublic relationsPsychologyPolitical scienceGeographyPsychiatry

Abstract

fetched live from OpenAlex

This paper describes an innovative new research program, Researching Health in Ontario Communities (RHOC), designed to improve understanding, treatment and prevention of co-occurring mental health, addictions, and violence problems. RHOC brings together a multi-disciplinary team of investigators to implement an integrated series of research studies (including pilot studies and full studies). The project involves use a mobile research laboratory to collect a wide range of biological, behavioral and social data in diverse communities across Ontario, Canada, including remote and rural communities, areas experiencing poverty and social disorganization, urban areas, and Aboriginal communities. This paper describes the project background and research plan as well as the anticipated contributions of the project to participating Ontario communities and to broader scientific knowledge.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.138
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.640
GPT teacher head0.572
Teacher spread0.068 · 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