Bibliographic record
Abstract
Migraine with aura (MA) arises from a combination of genetic and environmental factors. The sibling risk, age at onset, and aura type were compared in 54 MA probands categorised by family history of MA. Three family types were ascertained each having an MA proband and: (1) an MA parent and MA offspring (three generation; n=15), (2) either an MA parent or an MA offspring (two generation; n=20), and (3) neither an MA parent nor an MA offspring (one generation; n=19). The crude recurrence risk to siblings of probands was 2.7-fold higher in three generation compared with two generation MA families (chi(2)=6.24, p=0.0125) and 4.8-fold higher in three generation compared with one generation MA families (chi(2)=9.95, p<0.002). The mean age at onset decreased with an increase in genetic load. The MA probands from three generation families were significantly younger than probands from the one generation families (F=5.14, p=0.030). MA probands from three generation families were more likely to report more than one type of aura than MA probands from two generation families (chi(2)=4.44, p=0.035). The significant difference in genetic loading and the earlier age at onset in the three generation families add further evidence for a genetic basis for MA and the difference in sibling risks demonstrates that the MA population is heterogeneous.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".