Bibliographic record
Abstract
Oncology nursing, like many other nursing fields, often provides nurses with the opportunity to get to know their patients and their families well. This familiarity allows oncology nurses to show a level of compassion and empathy that is often helpful to the patient and their family during their struggle with cancer. However, this familiarity can also lead to a profound sense of grief if the patient loses that struggle. This self-study provided me the opportunity to systematically explore my own experience with grief as an oncology nurse, helping me to identify specific stressors and also sources of stress release. Oncology nursing, like many other nursing fields, often provides nurses with the opportunity to get to know their patients and their families well. This familiarity allows oncology nurses to show a level of compassion and empathy that is often helpful to the patient and their family during their struggle with cancer. However, this familiarity can also lead to a profound sense of grief if the patient loses that struggle. This self-study provided me the opportunity to systematically explore my own experience with grief as an oncology nurse, helping me to identify specific stressors and also sources of stress release.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".