Bibliographic record
Abstract
family challenged the health care team’s recommendations and insisted that their mother be readmitted to the ICU so that aggressive life-sus-taining treatment would continue. This case, although Canadian, is relevant to ICU settings throughout North America. The purpose of this discussion is not to provide an in-depth ethical analysis, but rather to use the case of Mrs H to character-ize one type of health care situation that clinical ethicists could help facilitate. Medical recommenda-tions such as those involved in the care of Mrs H are made to prevent the “revolving door ” patient, who according to ICU teams will receive no medical benefit if returned to the ICU. Decisions not to readmit are euphemistically referred to by some ICU staff as the “one-way ticket out of ICU ” or “celestial transfer. ” Such language shared between colleagues reflects a coping strategy, a “gallows humor, ” intended to manage diffi-cult feelings like sadness, anger, grief, sympathy, or moral distress. Cases like that of Mrs H are of
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.
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 | 0.083 | 0.102 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.023 | 0.073 |
| Scholarly communication | 0.026 | 0.011 |
| Open science | 0.003 | 0.020 |
| Research integrity | 0.014 | 0.022 |
| Insufficient payload (model declined to judge) | 0.010 | 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".