Palliative care programs for patients with breast cancer: the benefits of home-based care
Bibliographic record
Abstract
SUMMARY Improving breast cancer care means enhancing end-of-life care with specialized palliative care services. Palliative care embodies a holistic approach to care that focuses on symptom management of individuals with incurable diseases, whereas end-of-life care specifically focuses on a period of time, such as the last 6 months of life, where a rapid state of decline is often evident. The purpose of this article is to explore the benefits and limitations of end-of-life care provided in the hospital and community settings, with an emphasis on the benefits of home-based care. A key strength of home-based palliative care is the ability to expand the reach of palliative care to more cancer patients beyond residential hospice or hospital settings, which are limited in bed availability. The essential features of quality end-of-life services, regardless of setting, are care that offers seamless transitions, around-the-clock access to the same providers and an interdisciplinary, whole-person approach.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".