<i>Announcement:</i> Get Smart About Antibiotics Week — November 14–20, 2016
Bibliographic record
Abstract
November is National Epilepsy Awareness Month, and November 11 is Veterans Day.Epilepsy is a brain disorder that causes recurrent seizures, which are characterized by sudden, abnormal electrical activity in the brain that briefly changes the way a person behaves, thinks, or feels.Epilepsy affects 7-10 per 1,000 persons, or approximately 2.9 million persons in the United States (1,2).Although the prevalence of epilepsy in veterans is unknown, the Veterans Health Administration (VHA) estimates that during 2012-2014, the prevalence of epilepsy among veterans under treatment at VHA facilities was 13.9 per 1,000 persons (3).Approximately 13% of veterans with seizures were aged <45 years, 39% were aged 45-65 years, and 7% were female (3).Veterans are at higher risk for developing epilepsy than nonveterans because of an increased likelihood of traumatic brain injuries and post-traumatic stress disorder (4); these conditions are also associated with psychogenic nonepileptic seizures (events caused by psychological distress that resemble seizures, but are not associated with abnormal electrical activity in the brain).In a study published in this issue, veterans with epilepsy who were deployed in the Iraq and Afghanistan conflicts were found to have a higher prevalence of mental and physical comorbidity and substantially higher mortality than were veterans without epilepsy.The VHA Epilepsy Centers of Excellence (ECoE), a network of 16 sites that was created in 2008, provides comprehensive treatment and support to veterans with epilepsy (i.e., seizure disorders, including psychogenic nonepileptic seizures) (3).The ECoE's video series, Veterans and Epilepsy: Basic Training, helps educate veterans, their caregivers, and the general public about living with epilepsy, and helps reduce epilepsy-associated stigma (5).CDC supports community-based resources and services for all adults with epilepsy and evaluates epilepsy self-management programs for veterans with epilepsy.Information about these services and programs is available at http://www. cdc.gov/epilepsy.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.327 | 0.192 |
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".