Changes in gait and symptoms after bilateral pallidotomy: a client with Parkinson's disease
Bibliographic record
Abstract
A single-subject, time-series design was used to describe a female with young-onset Parkinson's disease who, after a period of 15 years, was demonstrating long term side effects of medication in addition to the progression of Parkinson's disease. She underwent a bilateral pallidotomy to address these problems. Prior to her surgery, her spatiotemporal gait kinematics were measured at intervals before and after medication ingestion. The identical procedures were undertaken one month and at four months post-pallidotomy. In all three sessions, the Webster Scale scored her symptoms while her medication was not working (Off) and again when effective (On). After surgery, she was interviewed to obtain a qualitative impression of the outcome. Before the surgery, the gait parameters demonstrated a fluctuating profile. Forty-five minutes post-medication, her gait parameters approached normal levels but significant dyskinetic movements were evident. Her Webster Scale scores indicated advanced Parkinson's disease particularly when Off One-month post-pallidotomy, her gait parameters were more consistent with dyskinesias mildly present. Her Webster Scale scores were reduced while both Off and On. Four months post-pallidotomy her gait parameters were entirely consistent and within normal limits. Her Webster Scale scores were the same Off and On and no dyskinesias were detectable. The excellent result was probably enhanced by the patient's dedication to regular exercise designed to minimize secondary physical complications.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".