<i>Z</i>-score of some pulsed-wave Doppler indices of right pulmonary artery segments of normal fetuses in the second and third trimestries
Bibliographic record
Abstract
To establish the Z-score equation of right pulmonary artery (RPA) segments for some valuable pulse-wave Doppler parameters (PWD) and estimate their reference ranges in normal fetuses. Two hundred and seventy-three normal singleton fetuses at 18–38 weeks were enrolled in this fetal echocardiography of a prospective cross-sectional study. The proximal, middle, and distal segments of RPA of pulsed-wave Doppler parameters, such as peak systolic velocity (PSV) and pulsation index (PI) were obtained by using fetal Doppler echocardiography. The mean and standard deviation (SD) of each parameter and gestational age (GA) were analyzed by regression, and the optimal model of Z-score was established. There was a significant correlation between fetal pulmonary artery Doppler parameters and gestational age, during the whole pregnancy, PI showed a downward trend with the progress of gestational week, while PSV showed an upward trend. Whether it was the original data or the data converted for the normal distribution of Z-score, the model that best described the mean value of parameters was quadratic regression. The SDs for PSV of the middle segment was a linear equation, others were constants. From proximal to distal of RPA, PSV showed a decreasing trend while PI showed an increasing trend. Z-score models and reference values for some PWD parameters of three segments of RPA were proposed against GA, which may quantitatively assess the flow dynamics of fetal RPA and quantitatively assess fetal lung circulation development and hemodynamic changes.
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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 | 0.001 | 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".