Protocol for a scoping review of triage approaches for patient referrals from primary to rheumatology care.
Bibliographic record
Abstract
This scoping review aims to identify and understand the extent and type of evidence related to triage approaches for patient referral from primary care physicians (PCP) to rheumatologists. Interventions have been designed to improve referrals from PCPs to rheumatologists. Triaging patients for proper referral and leveraging electronic health advancements creates new possibilities to reduce the burden of high-morbidity chronic diseases, such as inflammatory arthritis (IA). Since prompt appropriate rheumatology referrals for early intervention are known to improve outcomes in IA, there is an urgency to understand the types of action-ready triage approaches for healthcare implementation.
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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 | 0.077 | 0.111 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.009 | 0.013 |
| Bibliometrics | 0.017 | 0.015 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.177 | 0.027 |
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".