International consensus on ANA patterns (ICAP): the bumpy road towards a consensus on reporting ANA results
Bibliographic record
Abstract
The International Consensus on ANA Patterns (ICAP) was initiated as a workshop aiming to thoroughly discuss and achieve consensus regarding the morphological patterns observed in the indirect immunofluorescence assay on HEp-2 cells. One of the topics discussed at the second ICAP workshop, and addressed in this paper, was the harmonization of reporting ANA test results. This discussion centered on the issue if cytoplasmic and mitotic patterns should be reported as positive or negative. This report outlines the issues that impact on two major different reporting methods. Although it was appreciated by all participants that cytoplasmic and mitotic patterns are clinically relevant, implications for existing diagnostic/classification criteria for ANA-associated diseases in particular hampered a final consensus on this topic. Evidently, a more concerted action of all relevant stakeholders is required. Future ICAP workshops may help to facilitate this action.
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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 | 0.324 | 0.294 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.011 | 0.023 |
| Research integrity | 0.017 | 0.033 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".