Affective Disorders in Motor Neuron Disease: A Population-Based Study
Bibliographic record
Abstract
Several studies have suggested that there may be an increased prevalence of affective disorders in people with motor neuron disease (MND). However, the literature is inconsistent, possibly because of small sample sizes in the existing studies. The Canadian province of Alberta has a universal health care system in which physician contacts are recorded along with ICD-9-CM diagnostic codes. In this analysis, diagnostic codes indicative of MND and affective disorders were used. Stratified analysis and logistic regression were used in the analysis. There were 336 cases of MND leading to a prevalence of 14.5 per 100,000 in provincial residents > or =20 years old. Affective disorders were identified in 8.6% of the total population during the same year. The crude odds ratio for affective disorders in MND was 2.3 (95% CI = 1.7-3.0). However, the prevalence of affective disorders declined with increasing illness duration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".