Quantifying the effects of practicing a semantic task according to subclinical schizotypy
Bibliographic record
Abstract
Abstract Greater adaptability of patients should go with easier psychosocial rehabilitation. Medications should thus also be chosen according to their impact on practice effects, as they measure adaptability. We are thus developing a pre-treatment test aimed, in fine, at assessing the impact of medications on these effects. Here, we report the practice effects observed across the two sessions of a semantic categorization task. Participants (n = 47) completed the Schizotypal Personality Questionnaire (SPQ) and performed this task twice, 1.5 hours apart. Practice was found to reduce reaction times in both low- and high-SPQ scorers. It was also found to decrease the amplitudes of the N400 event-related brain potentials elicited by semantically matching words in low SPQ scorers only, which showed the sensitivity of the task to schizotypy. Both RTs and N400 amplitudes were also found to have a good test-retest reliability across the two sessions. This task could thus be a valuable tool. On-going studies are assessing the impacts of fully deceptive placebos and of real antipsychotic medications on these effects of practice. This should, later, help psychiatrists to choose the best medication for the psychosocial rehabilitation of a patient.
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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 | 0.005 |
| 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) | 0.002 | 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".