Proceedings of the 2020 GRAPPA Collaborative Research Network (CRN) Meeting
Bibliographic record
Abstract
At the 2020 Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA)-Collaborative Research Network (CRN) annual meeting, the GRAPPA-CRN group presented a pilot investigator-initiated study protocol to test electronic case report forms (eCRFs) and proposed Standardized Operating Procedures (SOPs) to evaluate biomarkers of psoriatic arthritis (PsA) associated with axial disease. The progress on 3 studies was also presented: BioDAM PsA (Biomarkers as Predictors of structural DAMage in PsA; to validate soluble biomarkers as predictors of structural damage in PsA), PreventPsA (examining the development of PsA and risk factors among patients with psoriasis and no arthritis), and PredictORPsA (Predicting Treatment respOnse in patients with eaRly PsA; in collaboration with Pfizer using samples from the Oral Psoriatic Arthritis TriaL [OPAL], to identify biomarkers of treatment response). GRAPPA-CRN funding partnerships and applications are also underway with both the Innovative Medicines Initiative (IMI) in Europe and Accelerating Medicines Partnerships (AMP) 2.0 in the USA, and the progress of these applications and associated objectives were presented.
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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 | 0.031 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.051 | 0.019 |
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".