Financial Resources Digital Navigation Tool for Metastatic Breast Cancer Patients
Bibliographic record
Abstract
Background and context: Although Canadians enjoy a universal health care system, there continues to be costs to patients that are not covered by the system. The economic impact of breast cancer is huge and, in many cases, devastating for patients and their families. As a result there is a need for educational and navigational resources that assist patients with the financial burden of facing a metastatic breast cancer diagnosis. Aim: The aim of this project is to develop an online navigation tool that will assist Canadians living with metastatic breast cancer source financial supports and resources to help lessen the financial impact of their diagnosis. Strategy/Tactics: An advisory board of people living with metastatic breast cancer was convened to help guide this project and provide input on the lived experience and financially challenges of Canadians living with this stage of the disease. The input from the advisory board along with the responses from a survey of over 150 Canadian metastatic breast cancer patients informed the type of information that should be included in the resource. Through an environmental scan and research of various financial supports, a comprehensive list of financial resources available locally, regionally and nationally was compiled. This data were integrated into a database that will be accessed through an intuitive online interface that will be integrated with CBCN´s Web site. The advisory board reviewed the draft content and framework to ensure that identified needs and priorities have been addressed. All content was translated into French as this tool will be offered in both French and English. The anticipated launch of this resource is November 2018. Outcomes: CBCN anticipates that over 1200 people living with metastatic breast cancer will access this resource in the first year and that over 50 institutions will be informed that this tool is available for their patients. Given that this will be a unique resource, CBCN expects that patients, health care professionals and support workers will access this resource to better support people living with metastatic breast cancer. What was learned: This resource has not launched, but based on CBCN´s research and the feedback of the patient advisory board, it is understood that there is a great need for this financial resources navigation tool.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.057 | 0.008 |
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".