Bibliographic record
Abstract
As founding Co-Editors-in-Chief of the Journal of Patient-Reported Outcomes (JPRO), we are excited to announce the launch of a new journal sponsored by the International Society for Quality of Life Research (ISOQOL).JPRO is intended to complement and extend ISOQOL's existing journal, Quality of Life Research.Clearly, Quality of Life Research has a long and successful history of publishing research on methods and applications of health-related quality of life (HRQL) and patient-reported outcomes (PROs).Given increased HRQL and PRO research, and the wider application of these outcomes across a variety of health care and population health settings, there is a need for more publication outlets for scientifically sound PRO research.The aims and scope of the Journal of Patient-Reported Outcomes focus on high quality research in five major areas: (1) PROs in clinical trials; (2) applications of PROs in clinical practice; (3) patient, family, community and public engagement in PRO research; (4) qualitative studies on the development and application of PROs; and (5)social and behavioral determinants of health and PRO measures.These focus areas are only some examples of the types of papers that are considered for publication in JPRO.JPRO is a peer-reviewed journal, with occasional special non-peer reviewed articles relevant to the journal's aims and scope.
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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 | 0.055 | 0.158 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.020 | 0.009 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.017 | 0.026 |
| Insufficient payload (model declined to judge) | 0.006 | 0.006 |
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".