Ultrasound image attributes of human ovarian dominant follicles during natural and oral contraceptive cycles
Bibliographic record
Abstract
BACKGROUND: Computer-assisted analyses were used to examine ultrasound image attributes of human dominant ovarian follicles that developed during natural and oral contraceptive (OC) cycles. We hypothesized that image attributes of natural cycle follicles would quantitatively differ from those in OC cycles and that OC cycle follicles would possess image attributes indicative of atresia. METHODS: Dominant ovarian follicles of 18 clinically normal women were compared using transvaginal ultrasonography for the 7 days before ovulation during a natural cycle (n = 9) or the 7 days before peak estradiol in women using OC (n = 11). Follicles were analyzed using region and line techniques designed to compare the image attributes numerical pixel value (NPV), pixel heterogeneity (PH) and area under the curve (AUC). RESULTS: NPV was higher in OC cycle follicles with region analysis and tended to be higher with line analysis (p = 0.005 and p = 0.06, respectively). No differences were observed in two other image attributes (AUC and PH), measured with either technique, between natural and OC cycle follicles. CONCLUSION: The increased NPV value of OC cycle follicles and lack of differences in PH and AUC values between natural cycle and OC cycle follicles did not support the hypothesis that OC cycle follicles would show ultrasonographically detectable signs of atresia. Image attributes observed in OC cycle follicles were not clearly indicative of atresia nor were they large enough to preclude preovulatory physiologic status in OC cycle follicles.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 |
| 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 teacher head, 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".