Perceptions of BELONG as a supportive e‐platform used by women with gynecologic cancers
Bibliographic record
Abstract
Key points The unmet needs of women with gynecologic cancers (GCs) can be readily addressed using high quality e‐platforms This pilot study documents women with GC perceptions of BELONG ( https://belong.life/ )—a cancer navigation and support Application (or App) connecting patients diagnosed with various types of cancers Women ( N = 25), with GCs (stages I to IV), used the App for 8 weeks and completed the user Mobile Application Rating Scale Ratings of BELONG in domains of engagement, functionality, aesthetics, and information were high, with Ask an Oncologist , Ovarian Cancer Community , Clinical Trials , Treatment Information , and Support Resources representing the most frequently accessed topics As e‐platforms are developed at a rapid pace, users' input and evaluation of platform quality and utility should be prioritized
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".