Clinical datasets related DeNoPa olfaction, cerebrospinal fluid readouts and alpha-synuclein seeding aggregation assay
Bibliographic record
Abstract
These dataset files are associated with the manuscript: Mollenhauer B*, Li J*, Schade S, Weber S, Trenkwalder C, Concha-Marambio L, Tomlinson JJ, aSCENT-PD Investigators and Schlossmacher MG. Persistent Hyposmia as Surrogate for alpha-Synuclein-Linked Brain Pathology. Submitted 2023 3 files: Data dictionary.csv Baseline_cut.csv Time_cut.csv The file "Data dictionary.csv" contains description of the two data files and the variables within. Clinical data used for this study is from the DeNoPa Cohort, led by Dr. Brit Mollenhauer, Department of Neurology, University of Goettingen, Kassel, Germany and the Paracelsus-Elena-Klinik. See references below for additional details. Mollenhauer B, Trautmann E, Sixel-Döring F, Wicke T, Ebentheuer J, Schaumburg M, Lang E, Focke NK, Kumar KR, Lohmann K, Klein C, Schlossmacher MG, Kohnen R, Friede T, Trenkwalder C; DeNoPa Study Group. Nonmotor and diagnostic findings in subjects with de novo Parkinson disease of the DeNoPa cohort. Neurology. 2013 Oct 1;81(14):1226-34. doi: 10.1212/WNL.0b013e3182a6cbd5 Concha-Marambio L, Weber S, Farris CM, Dakna M, Lang E, Wicke T, Ma Y, Starke M, Ebentheuer J, Sixel-Döring F, Muntean ML, Schade S, Trenkwalder C, Soto C, Mollenhauer B. Accurate Detection of α-Synuclein Seeds in Cerebrospinal Fluid from Isolated Rapid Eye Movement Sleep Behavior Disorder and Patients with Parkinson's Disease in the DeNovo Parkinson (DeNoPa) Cohort. Mov Disord. 2023 Apr;38(4):567-578. doi: 10.1002/mds.29329
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.086 | 0.041 |
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".