Integration through a city-wide brain injury network and best practices project
Bibliographic record
Abstract
Integration of systems of service for individuals who have sustained a brain injury (BI) is critical to their successful recovery and reintegration into the community [6,7,33]. The Toronto Acquired Brain Injury (ABI) Network, an umbrella organization of 17 partners in the city of Toronto, Canada, is attempting to create a cost-effective, seamless, efficient, and effective integrated system of service. The ABI Network includes organizations and agencies along the full continuum, from acute care inpatient to long term care reintegration and is ultimately focused on helping clients achieve their goals. Through a variety of projects and activities, progress is being made. A significant initiative, currently underway, is the development of Network-wide best practices, related to assessment and outcomes, rooted in empirical evidence and current research. The project also integrates the perspectives of clients and families. The hope is that this initiative will result in enhanced consistency across programs, ensuring universal access to treatment and interventions following brain injury from the time of an individual's injury through integration into the community.
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".