Consensus paper of the WFSBP Task Force on Biological Markers: Criteria for biomarkers and endophenotypes of schizophrenia part I: Neurophysiology
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The neurophysiological components that have been proposed as biomarkers or as endophenotypes for schizophrenia can be measured through electroencephalography (EEG) and magnetoencephalography (MEG), transcranial magnetic stimulation (TMS), polysomnography (PSG), registration of event-related potentials (ERPs), assessment of smooth pursuit eye movements (SPEM) and antisaccade paradigms. Most of them demonstrate deficits in schizophrenia, show at least moderate stability over time and do not depend on clinical status, which means that they fulfil the criteria as valid endophenotypes for genetic studies. Deficits in cortical inhibition and plasticity measured using non-invasive brain stimulation techniques seem promising markers of outcome and prognosis. However the utility of these markers as biomarkers for predicting conversion to psychosis, response to treatments, or for tracking disease progression needs to be further studied.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it