Clinical detection of PSP, not only an “atypical parkinsonism”
Bibliographic record
Abstract
Progressive Supranuclear Palsy (PSP) is a neurodegenerative condition that manifest motor, cognitive, and behavioral symptoms. Patients often suffer from early postural instability with falls, diplopia associated with oculomotor dysfunction, apathy, impulsivity, slowness of movement and of thought, as well as memory and language/communication disturbances. With any of those clinical features, patients may seek health care at various medical specialties, not uncommonly, out from neurology clinics. Clinical diagnosis is possible when specific criteria are fulfilled which can only be accomplished by a systematic history taking, time course consideration, and detection of signs at physical neuro-examination. Up to 4-years delay in diagnosis has been reported often due to the difficulty in distinguishing PSP findings from those of Parkinson's and Alzheimer's disease (PD and AD) and preventing referral to specialized clinics. In this presentation, the audience will hear about the specific but not hardly detectable clinical features that people with PSP can manifest early in disease course, how those features progress during the mild-moderate stages of the disease, and how PSP might be distinguishable from PD and AD even after a few clinical encounters.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".