Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Healthcare systems worldwide are faced with improving quality of care and decreasing adverse events.1 Providing evidence from clinical research is necessary but not sufficient for the provision of optimal care.2 This finding has created interest in knowledge translation (KT), the scientific study of the methods for closing the knowledge-to-practice gap and the analysis of barriers and facilitators inherent in this process.2 There are many proposed theories and frameworks for achieving KT, which can be confusing.3 One conceptual framework developed by Graham et al builds on the commonalities found in an assessment of planned-action theories.4 This knowledge-to-action cycle (figure) comprises knowledge creation and action components. We describe the application of this knowledge-to-action framework to a common clinical challenge: preventing delirium in older adults hospitalised for hip fracture. Knowledge-to-action cycle Delirium occurs in 25–65% of hospitalised patients treated for acute hip fracture.5-7 These patients are at increased risk of death, longer hospital stay, hospital-acquired complications, persistent cognitive deficits, and discharge to long-term care.8-11 Several factors increase the risk of delirium, including older age, use of physical restraints, malnutrition, use of urinary catheters, and the addition of more than 3 new medications.12 Strategies to prevent delirium have been shown to be effective but are underused in practice. Since multiple factors usually contribute to the development of delirium, multicomponent interventions appear effective in its prevention.13 14 A Cochrane review of strategies to prevent delirium15 identified 1 study of a multicomponent intervention targeted towards older adults admitted with hip fractures.16 However, multicomponent interventions are challenging to implement and sustain in real world clinical settings. One strategy to …
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.
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | low |
| gpt | no category Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | low |
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 | 0.000 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it