First trimester dating by fetal heart rate assessment: a comparison with crown-rump length measurement
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to determine whether fetal heart rate (FHR) can be used to date pregnancies in the early first trimester using the gold standard of crown-rump length (CRL) dating as a reference. METHODS: This single center study evaluated women undergoing obstetrical ultrasounds between 4.5 and 8.5 weeks. FHR and gestational age (GA) based on CRL were obtained. Linear regression analysis and a Bland-Altman plot were used to demonstrate the relationship between the two measurements. A further simplified version of the relationship between CRL and FHR that may be clinically useful was calculated. RESULTS: 176 patients were included in the study. The Pearson correlation coefficient was 0.95, indicating a strong correlation between the two dating methods. The Bland-Altman plot demonstrated agreement across GA tested. A simple arithmetic formula of GA(weeks)=FHR (beats per minute)/20 was calculated. 169/176 patients had <4 days discrepancy between FHR- and CRL-based dating using this formula. CONCLUSION: We found that a simple formula based on FHR may accurately date early pregnancies. This method, if further validated, may represent an important tool for pregnancy dating.
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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 | 0.007 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".