Additional file 1 of The Revised Self-Monitoring Scale detects early impairment of social cognition in genetic frontotemporal dementia within the GENFI cohort
Bibliographic record
Abstract
Additional file 1: Figure S1. RSMS EX scores in each genetic carrier group, stratified by Global CDR® plus NACC FTLD scores. Significant differences from controls and within each carrier group are starred. Differences between carrier groups are not shown. Figure S2. RSMS SP scores in each genetic carrier group, stratified by Global CDR® plus NACC FTLD scores. Significant differences from controls and within each carrier group are starred. Differences between carrier groups are not shown. Figure S3. Negative correlations between RSMS total and CDR® plus FTLD NACC SOB scores were observed across all mutation carrier groups: C9orf72 (r = -0.67, p < 0.001), GRN (r = -0.59, p < 0.001), MAPT (r = -0.53, p < 0.001). Each dot represents one mutation carrier. Table S1. RSMS total test scores (mean and SD) in healthy controls split by age group. Table S2. Cumulative frequency of RSMS total test scores in healthy controls. Table S3. Adjusted mean differences in RSMS EX scores between the genetic groups stratified by Global CDR® plus NACC FTLD scores with 95% bias-corrected confidence intervals (significant values in bold). Table S4. Adjusted mean differences in RSMS SP scores between the genetic groups stratified by Global CDR® plus NACC FTLD scores with 95% bias-corrected confidence intervals (significant values in bold). Table S5. Correlation of RSMS total test score with cognitive tests. Significant results are in bold. Table S6. Positive neuroanatomical correlates of grey matter volume with the RSMS total score in each genetic group.
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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 | 0.001 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.699 | 0.075 |
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".