Bibliographic record
Abstract
Editor—The final hours of a dying patient may be spent in an emergency department.1 In 2001, 444 patients died en route or in the emergency departments of Edmonton, Alberta. The number of family members immediately affected by the disclosure of this news while in the department is perhaps double this or more. Family members often experience grief when death occurs there because the patients are often younger and the deaths sudden and unexpected.2 Ensuring a good death while the patient is in an emergency department is a multi-disciplinary endeavour that requires the help of nurses, social workers, pastoral care workers, and doctors. In a good death the patient's advance directive (if he or she has one) is respected, and the patient suffers minimally. Also, in a good death the patient's emotional concerns are addressed in a caring and compassionate manner. This may include informing the family of the patient's illness. Communicating with family members of critically ill patients can be challenging and stressful for both family members and healthcare providers.3 A caring and considerate approach to communication with family members about the patient's condition can perhaps help to minimise the development of potential pathological grief responses. Having family members present at the bedside of the patient as he or she undergoes resuscitation or medical care can facilitate in communication of death and critical illness. Family members never have to question whether everything was done.3 The dying patient may gain emotional benefit from the comfort of family presence.
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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 | 0.002 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.009 | 0.017 |
| Insufficient payload (model declined to judge) | 0.017 | 0.012 |
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".