Normalizing Endophenotypes of Schizophrenia: The Dip and Draw Hypothesis
Why this work is in the frame
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Bibliographic record
Abstract
Schizophrenia is a multifactorial complex genetic disorder generally characterized by a copious and polarized array of features that cause an anomalous perception of reality and social dysfunction. Timely and accurate diagnosis of schizophrenia can be obscured due to comorbidity and treatment is often unsatisfactory. Two models, the dopamine and glutamate hypothesis, attempt to explain the underlying mechanisms of the disease. Importantly, the hypotheses are not mutually exclusive and may work together in the manifestation of schizophrenia, each playing an independent role for a subset of symptoms. Finding causes of the disease has been extremely difficult, largely due to its phenomic complexity. As a consequence, psychiatrists have begun to document endophenotypes, quantifiable symptoms with a molecular basis, for the disease in attempts to deconstruct, simplify and focus schizophrenia research. Endophenotypes can be present in model organisms, allowing for elegant and controlled experimentation. A recently generated reversible animal model of aberrant dopaminergic activity provides support for a novel understanding of how the brain may respond to antipsychotics. A prediction herein named the dip and draw hypothesis is presented to explain discrepancies between the early and delayed-onset hypotheses of antipsychotic action. Although progress in schizophrenia research has been modest over the last century, the recent union of theory and technology may provide the potential for better treatment.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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