Physiological Differences in the Follicular, Luteal, and Menstrual Phases in Healthy Women Determined by Electrovestibulography: Depression, Anxiety, or Other Associations?
Bibliographic record
Abstract
Electrovestibulography (EVestG) recordings have been previously applied toward classifying and/or measuring the severity of several neurological disorders including depression with and without anxiety. This study's objectives were to: (1) extract EVestG features representing physiological differences of healthy women during their menses, and follicular and luteal phases of their menstrual cycle, and (2) compare these features to those observed in previous studies for depression with and without anxiety. Three EVestG recordings were made on 15 young healthy menstruating females during menses, and follicular and luteal phases. Three features were extracted, using the shape and timing of the detected spontaneously evoked vestibulo-acoustic field potentials. Using these features, a 3-way separation of the 3 phases was achieved, with a leave-one-out cross-validation, resulting in accuracy of > 72%. Using an EVestG shape feature, separation of the follicular and luteal phases was achieved with a leave-one-out cross-validation accuracy of > 93%. The mechanism of separation was not like that in previous depression analyses, and is postulated to be more akin to a form of anxiety and/or progesterone sensitivity.
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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) | 0.000 | 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 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".