Graham Roberts Study protocol: first ‘trials within cohort study’ for bladder cancer
Bibliographic record
Abstract
INTRODUCTION: Given the need for more bladder cancer research and the recently observed advantages of introducing the trials within cohort (TwiCs) design, the set-up of the Graham Roberts Study (Roberts Study) will provide valuable infrastructure to answer a wide variety of research questions of a clinical, mechanistic, as well as supportive care nature in the area of bladder cancer. METHODS: Using the TwiCs design, we will recruit patients aged 18 or older who are willing and able to provide signed informed consent and have a diagnosis of new or recurrent bladder cancer into this prospective cohort study. All patients must have a basic understanding of the English language. The following questionnaires will be collected at baseline and every 12 months subsequently: Functional Assessment of Chronic Illness Therapy for Bladder Cancer, the Functional Assessment of Chronic Illness Therapy-Fatigue, the Patient Heath Questionnaire-9, the standardised instrument for a generic health status (EQ-5D-5L), a Short Questionnaire to Assess Health-Enhancing Physical Activity and the Hertfordshire Short Questionnaire to Assess Diet Quality. ETHICS AND DISSEMINATION: Due to the nature of this study, we obtained full ethical clearance from the London-Fulham Research Ethics Committee (17/LO1975). All participants must provide full informed consent before recruitment onto the study. The results of this study will be published in peer-reviewed journals and data collected as part of the study will be made available to potential collaborators on an application basis.
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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 | 0.105 | 0.153 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.103 | 0.035 |
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".