Advances in Patient Reported Outcomes: Integration and Innovation
Bibliographic record
Abstract
Following the success of the previous three PROMs Research Conferences held at University of Sheffield (2016), St Anne's College, University of Oxford, (2017) and the Centre for Patient Reported Outcomes Research (CPROR) at the University of Birmingham, (2018), we report the proceedings from the 2019 conference held at Leeds Beckett University Centre for Psychological Research (PsyCen) on the 13 th June. Aims of the conference:To gather clinicians, patient partners, researchers, academics, leading international experts, and early career researchers to explore current advances and best practice in research and implementation in the PROM field in the UK and beyond.The overall theme of the conference was 'Advances in Patient Reported Outcomes:Integration and Innovation'. Summary of eventAltogether, 77 multi-disciplinary delegates attended including 6 patient representatives.The programme centred around two stimulating plenary sessions, a workshop, parallel oral sessions and poster exhibitions.
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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 | 0.053 | 0.094 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.011 |
| Insufficient payload (model declined to judge) | 0.043 | 0.007 |
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".