Course of illness, hippocampal function, and hippocampal volume in major depression
Bibliographic record
Abstract
Studies have examined hippocampal function and volume in depressed subjects, but none have systematically compared never-treated first-episode patients with those who have had multiple episodes. We sought to compare hippocampal function, as assessed by performance on hippocampal-dependent recollection memory tests, and hippocampal volumes, as measured in a 1.5-T magnetic resonance imager, in depressed subjects experiencing a postpubertal onset of depression. Twenty never-treated depressed subjects in a first episode of depression were compared with matched healthy control subjects. Seventeen depressed subjects with multiple past episodes of depression were also compared with matched healthy controls and to the first-episode patients. Both first- and multiple-episode depressed groups had hippocampal dysfunction apparent on several tests of recollection memory; only depressed subjects with multiple depressive episodes had hippocampal volume reductions. Curve-fitting analysis revealed a significant logarithmic association between illness duration and hippocampal volume. Reductions in hippocampal volume may not antedate illness onset, but volume may decrease at the greatest rate in the early years after illness onset.
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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 | 0.000 | 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".