Inequalities in End-Of-Life Care for Colorectal Cancer Patients in Nova Scotia, Canada
Bibliographic record
Abstract
Access to high-quality end-of-life (EOL) care is critical for all those with incurable cancer. The objective of this study was to examine inequalities in access to, and quality of, EOL care by assessing registration in a palliative care program, emergency room visits in the last 30 days of life, and location of death among individuals who died of colorectal cancer in Nova Scotia, Canada, between 2001 and 2008. We used population-based linked administrative data and performed multivariate logistic regression models to assess the association between socio-economic, geographic, and demographic factors and outcomes related to access to, and quality of, EOL care (n=1201). This study demonstrates that although access to, and quality of, EOL care appears to have improved, there remain significant inequalities throughout the population. Of primary concern is the variation in access to, and quality of, EOL care based on geographic location of residence and patient age.
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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 | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".