Moving Toward an Organized Approach to Patient Education in Canadian Hospitals
Bibliographic record
Abstract
Hospital care is part of a complex healthcare system that can be difficult for individuals to navigate (Institute of Medicine 2004). There is significant pressure on patients to make sense of information due to the increasing burden of chronic disease, an increasing need for individuals to manage their own care and an abundance of consumer health information from various sources (Institute of Medicine 2004). To meet these demands, patients require tailored health information to help them make informed decisions, develop basic self-care skills, recognize problems and know what to do (London 2009). Patient education plays a significant role in helping people to succeed in these tasks.
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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 | 0.013 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.032 | 0.008 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.006 | 0.015 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.019 | 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".