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Record W6925393947 · doi:10.17605/osf.io/evxt4

HEARTS Study - Quantitative Data 2

2025· article· en· W6925393947 on OpenAlexaboutno aff

Bibliographic record

VenueOSF Preprints (OSF Preprints) · 2025
Typearticle
Languageen
FieldMedicine
TopicMicrobial Natural Products and Biosynthesis
Canadian institutionsnot available
Fundersnot available
KeywordsConceptualizationEquity (law)Transparency (behavior)Health careTriageMental healthHealth dataSocializationData system

Abstract

fetched live from OpenAlex

This repository contains supplementary materials for the HEARTS Study - Quantitative Data 2, which examines healthcare access barriers for young adults with mental health-related disabilities (MHRD) in Canada. This is a critical realist study with a patient oriented approach to identify structural mechanisms of exclusion, including bureaucratic gatekeeping, triage models, and administrative complexity. This project provides access to the functional impairments and health system barriers chart, as well as supplementary data documenting the iterative development of a redefined conceptualization of access. The materials reflect empirical analysis, co-researcher engagement, interest-holder input, and socialization through national networks via LinkedIn, Instagram, and Facebook. These files support transparency and accessibility of the research outputs, making them available to researchers, policymakers, practitioners, and advocates working on health system equality, equity and disability inclusion.

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)0.031
metaresearch head score (Gemma)0.153
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.424
Threshold uncertainty score0.822

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0310.153
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.008
Science and technology studies0.0030.002
Scholarly communication0.0040.003
Open science0.0020.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.4240.056

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 head0.041
GPT teacher head0.331
Teacher spread0.290 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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