Correlations between ultrasonographic characteristics of corpora lutea and systemic concentrations of progesterone during the discrete stages of corpora lutea lifespan and secretory activity in cyclic ewes
Bibliographic record
Abstract
Associations between physical characteristics and functionality of corpora lutea (CL) have previously been reported in monovulatory species, albeit several studies in cattle and humans have refuted the existence of temporal relationships between CL size, echotexture and serum progesterone (P(4)) concentrations. The main objective of the present study was to examine whether or not there were correlations between ultrasonographic image attributes of CL and systemic concentrations of P(4) during the discrete stages of the luteal phase in two breeds of sheep differing in ovulation rates (non-prolific Western White Face [WWF] ewes and prolific Finn [F] sheep). Transrectal ovarian ultrasonography utilized a 7.5-MHz linear-array transducer connected to a portable scanner (Aloka SSD-500) and the images were analyzed using commercially available image analytical software (Image ProPlus(®)) validated for the present application in sheep. The correlations were assessed using the Pearson's Product Moment (PPM) analysis and also, to increase the accuracy of statistical tests, the analysis of covariance (ANCOVA), with the number of CL as a co-factor. In WWF ewes, serum concentrations of P(4) correlated significantly with the total luteal area (TLA) during the CL growth phase (days 3-6; day 0 = ovulation) and functional luteolysis (days 12-15), and with numerical pixel values (NPVs--pixel intensity) during luteolysis; the results obtained by using two different statistical methods were generally similar. In prolific F ewes, serum P(4) concentrations were directly correlated with TLA during CL growth (days 3-6; ANCOVA), functional luteolysis (days 13-14; PPM), and structural CL regression (days 11-14; PPM and ANCOVA), and with NPVs during functional luteolysis (PPM and ANCOVA). We concluded that systemic P(4) concentrations could only be accurately predicted from the changes in luteal area during CL growth and regression, and from NPVs during luteolysis, in both prolific and non-prolific ewes, but the changes in size and echotexture of the luteal glands at mid-cycle were not indicative of serum P(4) concentrations in sheep.
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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 | 0.001 | 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) | 0.000 | 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".