Predicting a Risk of Transition to a Higher Level of Care for Home Support Service Recipients
Bibliographic record
Abstract
This longitudinal, non-randomized, retrospective study uses the Kaplan-Meier estimates method and the Cox Proportional Hazard model to assess the risk of home support recipients' transitioning to a higher level of care after being hospitalized. The Kaplan-Meier survival analysis revealed that 50% of home support recipients were expected to move on to a higher level of care by day 1,374. The Cox Proportional Hazard model indicated that the risk of transitioning to a higher level of care increases by about 2% as a client ages by one year, and by about 10% if there were no emergency room visits in the last 12 months. Also, the risk will decrease by about 13% if an individual is getting more than one hour of home support service per visit on average, compared to those who are receiving less than one hour of home support services per visit. These results will help project long term home support demand and resource planning for home support and the health care system.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".