Assessing the Acute Effects of CDP-Choline on Sensory Gating and Cognitive Deficits in Chronic Schizophrenia
Bibliographic record
Abstract
Deficits as a Core Clinical FeatureSchizophrenia (SZ) is a chronic brain disorder affecting approximately 21 million people worldwide (WHO, 2015).It is characterized by a number of symptoms appearing heterogeneously.Primarily, SZ has come to be associated with positive symptoms and negative symptoms (Keefe & Fenton, 2007).Positive symptoms encompass disturbances of cognitive, sensory, or motor processes that are not commonly observed in healthy individuals.This would include many of the trademark symptoms associated with the disorder, namely hallucinations, delusions, and disorganized thought and speech.Negative symptoms refer to the deficit of normal behaviours.This would include such symptoms as apathy, social withdrawal, and flat affect.Recently, neurocognitive deficits have come to the forefront of SZ research and
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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 | 0.000 |
| 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".