Moving in for Renovations: An Innovative Solution for Replacing End-of-Life Capital Equipment. The Michael Garron Hospital – Sunnybrook Collaborative Catheterization Laboratory Project
Bibliographic record
Abstract
Replacement of an end-of-life cardiac catheterization laboratory ("cath lab") can pose a significant challenge to a hospital, particularly in single-cath-lab institutions. The disruption in patient care requires innovative approaches to minimize the inconvenience and ensure ongoing quality of care. We describe a unique approach whereby Michael Garron Hospital (MGH) "leased" a cath lab within Sunnybrook Health Sciences Centre for a 12-week period during a cath lab replacement project at MGH. The MGH cath lab and patient recovery bay remained a completely separate entity staffed by MGH nurses and physicians, with electronic connection to the home hospital. A total of 420 patients underwent cardiac catheterization with no adverse outcomes while maintaining system efficiency and high patient and staff satisfaction. Cath lab leasing involving two cooperating hospitals is an innovative and safe way to bridge a cath lab replacement.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".