Hippocampal volumetrics in treatment‐resistant depression and schizophrenia: The devil's in De‐Tail
Bibliographic record
Abstract
Studies of patients with major depressive disorder (MDD) and schizophrenia (SCH) have revealed reduced hippocampal volumes, but findings have been inconsistent due to sample and measurement differences. The current study sought to measure this structure in a large sample of MDD, SCH, and healthy subjects, using a strict measurement protocol, to elucidate morphological-specific volumetric differences. Patients with treatment-resistant MDD (N = 182) and treatment-resistant SCH with auditory-verbal hallucinations (N = 52), and healthy controls (N = 76) underwent psychiatric assessments and brain MRI. The findings indicate that (1) MDD and SCH patients have reduced total hippocampal volume which was marked in the tails (more so in patients with MDD), (2) region of interest estimation protocols and sample characteristics may help explain volumetric differences between previous SCH studies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".