Additional file 1 of Shared burden of ultra-rare genetic variants across a spectrum of motor neuron diseases
Bibliographic record
Abstract
Additional file 1. Supplementary methods. Supplementary results. Supplementary discussion. Fig. S1 Distributions of genetic ancestries, age of onset, and sites of onsets by sex. Fig. S2 The workflow of variant analyses in CReATe PGB1 whole genome sequencing pipeline. Fig. S3 Genetic architecture of the PGB1 Cohort. Fig. S4 Uniform coverage ensures reliable CNV detection in PGB1 WGS. Fig. S5 The workflow of variant prioritization to identify pathogenic and predicted disease-mediating ultra-rare variants. Fig. S6 Pathogenic and predicted disease-mediating URVs in disease associated genes in HSP patients. Fig. S7 Pathogenic and predicted disease-mediating URVs in disease-associated genes in ALS and HSP, by ancestry background. Fig. S8 Association of URVs of various categories to age of onset of ALS and HSP. Fig. S9 Rare variant burden test to estimate the genetic risk conferred by URVs in randomized gene sets.
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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 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| 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) | 0.856 | 0.162 |
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".