Research to Integrate Services for Individuals with Traumatic Brain Injury, Mental Health, and Addictions: Proceedings of a MultiDisciplinary Workshop
Bibliographic record
Abstract
We present the findings from a one-day, multidisciplinary meeting to gather feedback for an integrated knowledge translation research project addressing the integration of health services and supports for individuals with traumatic brain injury, mental health, and/or addictions; especially those who experience homelessness/vulnerably housed, intersect with the criminal justice system, and are survivors of intimate partner violence. This meeting brought together persons with lived experience, service providers, decision makers, and researchers, who provided feedback that further refined the research methodology and highlighted existing gaps. This event was successful in inviting collaboration, knowledge exchange and dissemination, and advancing an important knowledge-to-action cycle for this research.
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 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 | 0.135 | 0.116 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.037 | 0.012 |
| Scholarly communication | 0.016 | 0.008 |
| Open science | 0.007 | 0.030 |
| Research integrity | 0.013 | 0.024 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
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".