Asymmetrical hand force persistence and neuroleptic treatment in schizophrenia
Bibliographic record
Abstract
The recent development of an isometric instrument for the precise quantification of hand force persistence has created a novel opportunity for the evaluation of potential motor asymmetries in schizophrenia and their response to treatment. A study of asymmetries in the unmedicated state may provide insight into the pathogenesis of schizophrenia, whereas alterations of asymmetries in response to antipsychotic medication could assist the delineation of a cerebral mechanism for the effects of pharmacotherapy. The hand force persistence of 21 unmedicated patients with schizophrenia was compared to 21 age, gender, and handedness matched normal controls. The effect of neuroleptic treatment on hand force persistence was then evaluated on a subset of 10 patients after at least 30 days of treatment. The anticipated asymmetry was evident in the unmedicated sample that showed impaired right hand force persistence compared to the normal control sample. The prospective comparison showed an alleviation of the asymmetry resulting from an improvement of right hand force persistence with treatment. In addition to providing further support to a primary left hemisphere cerebral involvement in schizophrenia, the present results suggest that prior investigations of motor asymmetry may have been compromised by the study of medicated patients. The apparently paradoxical improvement of motor skill may relate to the substantial number of patients treated with 2nd generation neuroleptic medications which may implicate an improvement in left hemisphere physiology in the cognitive advantages of the novel treatments.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".