Ventilator withdrawal for reallocation during a covid-19 surge needs a deeper discussion
Bibliographic record
Abstract
Many jurisdictions around the world have developed ventilator triage protocols in the event that demand for ventilation during the COVID-19 pandemic overwhelms the available supply. These protocols would be used to determine which patients get priority access to potentially life-saving ventilation. One particularly controversial element of these protocols is what we refer to as “withdrawal for reallocation” – that is, the practice of withdrawing a ventilator from one patient in order to provide it to another patient with a comparatively higher likelihood of benefit. This element raises several ethical issues that have not been given due consideration in the protocols themselves and the literature on the topic. In this paper we highlight these issues and provide recommendations for addressing them. © 2021, University of Toronto. All rights reserved.
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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 | 0.072 | 0.160 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.017 |
| Scholarly communication | 0.011 | 0.015 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.020 | 0.026 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".