Improving care and wellness in bipolar disorder: origins, evolution and future directions of a collaborative knowledge exchange network
Bibliographic record
Abstract
The Collaborative RESearch team to study psychosocial factors in bipolar disorder (CREST.BD) is a multidisciplinary, cross-sectoral network dedicated to both fundamental research and knowledge exchange on bipolar disorder (BD). The core mission of the network is to advance the science and understanding of psychological and social issues associated with BD, improve the care and wellness of people living with BD, and strengthen services and supports for these individuals. CREST.BD bridges traditional and newer research approaches, particularly embracing community-based participatory research (CBPR) methods. Membership of CREST is broad, including academic researchers, people with BD, their family members and supports, and a variety of health care providers. Here, we describe the origins, evolution, approach to planning and evaluation and future vision for our network within the landscape of CBPR and integrated knowledge translation (KT), and explore the keys and challenges to success we have encountered working within this framework.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.055 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.016 |
| Scholarly communication | 0.017 | 0.017 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".