P.041 First Degree Movement Disorders Cases and Research
Bibliographic record
Abstract
Background: While researchers pursue the etiology, pathophysiology and treatment of movement disorders, presently there is no biological marker for the two most common disorders – essential tremor (ET), and Parkinson’s disease and variants (Parkinson syndrome, or PS). The diagnosis of each remains clinical, but definitive diagnosis is made on brain pathology. Population epidemiological studies are hampered by a lack of diagnostic precision. Twins with the same disorder are scarce, and the next best option is studies of well-documented first-degree family members. Methods: Patients were seen at the Saskatchewan Movement Disorders Program (SMDP). All autopsied cases with known clinicopathological diagnosis of a movement disorder between 1970 and 2019 were reviewed. Only those with a first-degree family member – parent, child, and/or sibling - with a movement disorder were included. Results: 671 cases with movement disorders seen at SMDP have been autopsied. 29 cases including probands were found and thirteen first-degree families were identified; eight families were multiple (2 or more) siblings and five families included one parent/one child. In seven families, the diagnosis was concordant. Conclusions: Movement disorders in first degree relatives with autopsied verified diagnosis are dissimilar in nearly half the cases. Such small intensively studied groups offer unique research opportunities.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".