Normalized electroencephalogram power: a trait with increased risk of dementia
Bibliographic record
Abstract
Journal Article Normalized electroencephalogram power: a trait with increased risk of dementia Get access Magdy Younes, Magdy Younes Sleep Disorders Center, Misericordia Health Center, University of Manitoba, Winnipeg, Canada Corresponding author. Magdy Younes, 255 Wellington Crescent, unit 1105, Winnipeg, Manitoba, R3M 3V4, Canada. Email: mkyounes@shaw.ca. Search for other works by this author on: Oxford Academic Google Scholar Susan Redline, Susan Redline Departments of Medicine, Neurology and Psychiatry, Brigham and Women's Hospital, Boston MA, USA https://orcid.org/0000-0002-6585-1610 Search for other works by this author on: Oxford Academic Google Scholar Katherine Peters, Katherine Peters California Pacific Medical Center Research Institute, San Francisco CA, USA Search for other works by this author on: Oxford Academic Google Scholar Kristine Yaffe, Kristine Yaffe Departments of Psychiatry, Neurology, and Epidemiology and Biostatistics, University of California, San Francisco, CA, USA Search for other works by this author on: Oxford Academic Google Scholar Shaun Purcell, Shaun Purcell Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Harvard University, Boston, USA and Search for other works by this author on: Oxford Academic Google Scholar Ina Djonlagic, Ina Djonlagic Sleep Disorders Center, Beth Israel Deaconess Medical Center, Boston, MA, USA Search for other works by this author on: Oxford Academic Google Scholar Katie L Stone Katie L Stone California Pacific Medical Center Research Institute, San Francisco CA, USA Search for other works by this author on: Oxford Academic Google Scholar Sleep, Volume 46, Issue 12, December 2023, zsad195, https://doi.org/10.1093/sleep/zsad195 Published: 20 July 2023 Article history Published: 20 July 2023 Corrected and typeset: 11 August 2023
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".