Form and function of the corpus luteum during the human menstrual cycle
Bibliographic record
Abstract
OBJECTIVE: To characterize the growth and regression of the corpus luteum (CL) during an interovulatory interval (IOI) using serial transvaginal ultrasonography. METHODS: Fifty healthy women of reproductive age with a history of regular menstrual cycles underwent daily transvaginal ultrasonography for one IOI. Measurements of luteal area and luteal numerical pixel value (NPV) were recorded each day after ovulation until the CL could no longer be detected. Blood was drawn every third day during the IOI to measure serum concentrations of progesterone and estradiol-17beta. RESULTS: Corpora lutea were of two morphological types: those with a central fluid-filled cavity (CFFC) (78%) and those without (22%). Eighty-eight percent of women exhibited a CL containing a CFFC 2 days after ovulation, followed by 34% 13 days after ovulation and 2% 27 days after ovulation. Luteal area, progesterone concentration and estradiol concentration increased for approximately the first 6 days following ovulation followed by a subsequent decline. Luteal NPV decreased from days 1 to 11 and increased during days 11-16. Changes in luteal area, NPV, progesterone and estradiol concentrations did not differ in women with two versus three waves of follicular development. CONCLUSIONS: Peak luteal function, as determined by maximum luteal area, progesterone concentration and estradiol concentration, is observed 6 days following ovulation. Luteal NPV is reflective of morphological and endocrinological changes in the CL. The development of a CFFC during luteinization is a normal physiological phenomenon. The CL can be detected, but is not functional, 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 | 0.000 |
| 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".