Shared-care model for complex chronic haematological malignancies
Bibliographic record
Abstract
Myeloproliferative neoplasms (MPNs) are a group of rare Philadelphia-negative chronic leukemias. Disease rarity has resulted in limited expertise concentrated in specialist centres. Patients are often referred to such expert centres for diagnostic issues, complex decision-making, access to novel drugs through clinical trials, and supportive care. Attending such appointments may increase financial and travel burden, increase caregiver stress, and negatively impact quality of life. To address this, the MPN program at Princess Margaret (PM) Cancer Centre has implemented a shared-care model, working with local healthcare providers to provide ongoing management, and supportive care for MPN patients closer to home. This decreases patient travel burden, while maintaining high-quality patient-centered care. In this article we share our experience implementing the shared-care model. This model is potentially applicable to other chronic hematological malignancies and rare chronic diseases. The ultimate goal of shared-care is not to centralize care, but instead to build a community of accessible care for the patient.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.015 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".