Three-dimensional magnetic resonance imaging for the study of ovarian function in a bovine in vitro model
Bibliographic record
Abstract
Three-dimensional magnetic resonance imaging coupled with maximum intensity projection display, a technique usually reserved for magnetic resonance imaging angiography, is useful for the study of ovarian follicular growth. The ovaries of 19 cows were examined each day by transrectal ultrasonography. From these data, the precise phase of the ovarian cycle was determined and cows were ovariectomized on day 3 of wave one (n = 5), on day 6 of wave one (n = 4), on day 1 of wave two (n = 4), >/= 17 days after ovulation (n = 5), and on the day of ovulation (n = 1). The excised ovaries were examined by magnetic resonance imaging using a fast imaging with steady state precession imaging sequence with maximum intensity projection reconstruction, displayed as a cine-loop of the ovaries rotating in space. This provided the clearest view among the three principal three-dimensional steady state data acquisition approaches tried; the follicles and other ovarian structures could be distinguished unambiguously. Results from the bovine model indicate that the acuity of the three-dimensional fast imaging with steady state precession technique has potential application in in vivo intravaginal imaging in women for studying normal and pathological ovarian function.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.000 |
| 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 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".