Additional file 1 of Diagnostic delay of myositis: an integrated systematic review
Bibliographic record
Abstract
Additional file 1. Supplementary table 1. Search string conducted on Pubmed/Medline. Supplementary table 2. Data extraction tool. Supplementary table 3. Adapted version of Newcastle-Ottawa score. Supplementary table 4. Data extraction summary of selected studies. Supplementary table 5. Meta-aggregation results of initial symptoms by subtypes of IIM. Factors identified in case studies as related to diagnostic delay. Supplementary table 6. Factors identified in case studies as related to diagnostic delay. Supplementary table 7. Factors of diagnostic delay by myositis types. Supplementary figure 1. Adapted version of Newcastle-Ottawa score. Supplementary figure 2. Contour-Enhanced funnel plot for mean diagnostic delay in diagnosis (n = 19). Supplementary figure 3. Forrest plot for mean diagnostic delay in all studies reporting standard deviation (no = SD not estimated, yes = SD estimated). Supplementary figure 4. Forrest plot for mean diagnostic delay in MSA tested and not tested studies. Supplementary figure 5. forrest plot for mean diagnostic delay in Peter Bohan's criteria and ENMC criteria. Supplementary figure 6. Forrest plot for mean diagnostic delay in multidisciplinary and specialist centres. Review protocol: Diagnostic delay of myositis: a protocol of an integrated systematic review.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.081 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.013 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.711 | 0.030 |
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".