In the aftermath of a perioperative death: who cares for the clinician?
Bibliographic record
Abstract
Working in the perioperative environment entails exposure to traumatic and sometimes catastrophic events such as a perioperative death (PD). PD can be a uniquely devastating experience and has the potential to lead to long-term negative physical and psychological effects for the staff involved, especially when appropriate support is absent. In a number of practice settings, these destabilizing effects have been shown to detrimentally compromise individual and team performance.1 This is of particular concern in the perioperative setting, since deterioration of individual competence and subsequent team performance has been directly linked to poor patient outcomes. Despite numerous studies establishing this link, there has been little research exploring clinicians' experiences of PD and organisational support for front-line clinicians remains alarmingly inconsistent. The question remains, who is responsible to the clinician in the aftermath of a perioperative death?
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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 | 0.007 | 0.047 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.022 | 0.027 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".