Characterization of Ovarian Follicular Wave Dynamics in Women1
Bibliographic record
Abstract
A wave phenomenon of ovarian follicular development in women has recently been documented in our laboratory. The objective of the present study was to characterize follicular waves to determine whether women exhibit major and minor wave patterns of follicle development during the interovulatory interval (IOI). The ovaries of 50 women with clinically normal menstrual cycles were examined daily using transvaginal ultrasonography for one IOI. Profiles of the diameters of all follicles >or=4 mm and the numbers of follicles >or=5 mm were graphed during the IOI. Major waves were defined as those in which one follicle grew to >or=10 mm and exceeded all other follicles by >or=2 mm. Minor waves were defined as those in which follicles developed to a diameter of <10 mm and follicle dominance was not manifest. Blood samples were drawn to measure serum concentrations of estradiol-17beta, LH, and FSH. Women exhibited major and minor patterns of follicular wave dynamics during the IOI. Of the 50 women evaluated, 29/34 women with two follicle waves (85.3%) exhibited a minor-major wave pattern of follicle development and 5 women (14.7%) exhibited a major-major wave pattern. Ten of the 16 women with three follicle waves (62.5%) exhibited a minor-minor-major wave pattern, 3 women (18.8%) exhibited a minor-major-major wave pattern, and 3 women (18.8%) exhibited a major-major-major wave pattern. Documentation of major and minor follicular waves during the menstrual cycle challenges the traditional theory that a single cohort of antral follicles grows only during the follicular phase of the menstrual cycle.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".