Additional file 1 of Geo-epidemiology of autoantibodies in rheumatoid arthritis: comparison between four ethnically diverse populations
Bibliographic record
Abstract
Additional file 1: Supplementary Figure 1. AMPA and control peptide reactivity in RA and HCs. Levels in arbitrary units (aU/mL) for four AMPAs in the serum of four ethnically diverse RA populations and their ethnicity-matched healthy controls (HC). Grey dots indicate reactivity to the control peptide that was tested in tandem with the AMPA (which are shown with black dots). Blue violin plots display the median, interquartile range, and distribution of levels.NL: Netherlands, FN: First Nation, JP: Japan, SA: South Africa, RA: RA patients, HC: healthy controls. Supplementary Figure 2. Autoantibody levels in patients seropositive for each AMPAs in ethnically diverse RA populations. Levels in arbitrary units (aU/mL) for four AMPAs in the serum of four ethnically diverse RA populations. Patients clustered at the maximum were above the highest standard of the ELISA. Grey shading indicates the cohort-specific cut-off (see Supplementary Figure 2 for data regarding cut-off determination in healthy controls and reactivity to the control peptide). Lines indicate median and interquartile range and p-values correspond to Mann-Whitney U tests. Supplementary Figure 3. Autoantibody levels in patients seropositive for each AMPAs in ethnically diverse RA populations. Ratios of levels in arbitrary units (aU/mL) for four AMPAs per grams per liter (g/L) total IgG in the serum of four RA populations. Ratios are only shown in patients that were positive for the AMPA and that were also not above the highest standard. Lines indicate median and interquartile range; p-values correspond to Mann-Whitney U tests. The range of aU/mL per g/L are not directly comparable between AMPAs.
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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 | 0.002 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.818 | 0.102 |
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".