The neurobiology of treatment-resistant schizophrenia: paths to antipsychotic resistance and a roadmap for future research
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
Treatment-resistant schizophrenia (TRS), the persistence of positive symptoms despite ≥2 trials of adequate dose and duration of antipsychotic medication with documented adherence, is a serious clinical problem with heterogeneous presentations. TRS can vary in its onset (at the first episode of psychosis or upon relapse), in its severity, and in the response to subsequent therapeutic interventions (i.e., clozapine, electroconvulsive therapy). The heterogeneity of TRS indicates that the underlying neurobiology of TRS may differ not only from treatment-responsive schizophrenia but also among patients with TRS. Several hypotheses have been proposed for the neurobiological mechanisms underlying TRS, including dopamine supersensitivity, hyperdopaminergic and normodopaminergic subtypes, glutamate dysregulation, inflammation and oxidative stress, and serotonin dysregulation. Research supporting these hypotheses is limited in part by variations in the criteria used to define TRS, as well as by the biological and clinical heterogeneity of TRS. Clinical trial designs for new treatments should be informed by this heterogeneity, and further clinical research is needed to more clearly understand the underlying neurobiology of TRS and to optimize treatment for patients with TRS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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