The Gulf War era multiple sclerosis cohort: 3. Early clinical features
Bibliographic record
Abstract
OBJECTIVES: To present clinical features at diagnosis for a large nationwide incident cohort of multiple sclerosis (MS) among those serving in the US military during the Gulf War era (GWE). MATERIALS & METHODS: Medical records and databases from the Department of Veterans Affairs (VA) for cases of MS with onset in or after 1990, active duty between 1990 and 2007 and service connection by the VA, were reviewed for diagnosis and demographic variables. Neurological involvement was summarized by the Kurtzke Disability Status Scale (DSS) and the Multiple Sclerosis Severity Score (MSSS). RESULTS: Among 1919 cases of clinically definite MS, 94% had a relapsing-remitting course and 6% were primary progressive at diagnosis. More males of all races and blacks of both sexes were progressive. At diagnosis, functional system involvement was pyramidal 69%, cerebellar 58%, sensory 55%, brainstem 45%, bowel/bladder 23%, cerebral 23%, visual 18%, and other 5%. Mean DSS scores were: white males, females 2.9, 2.7; black males, females 3.3, 2.8; and other-race males, females 3.2, 2.6. Mean and median MSSS were marginally greater in black males and other males compared to the other sex-race groups. CONCLUSIONS: In this incident cohort, males and blacks had significantly higher proportions of primary progressive MS. DSS at diagnosis was significantly more severe in blacks and significantly less so in whites and in women vs men, but MSSS was only marginally greater in black males and other-race males. This morbidity assessment early in the course of MS provides population-based data for diagnosis, management, and prognosis.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".