Natural procreative technology for infertility and recurrent miscarriage
Bibliographic record
Abstract
To study the outcomes of women with infertility or miscarriage treated with natural procreative technology (NaProTechnology or NPT), a systematic medical approach to promoting conception in vivo; and to compare the outcomes with those previously published from a general practice in Ireland. Results A total of 108 couples received NPT and were included in the analysis, of which 19 (18%) reported having 2 or more previously unexplained miscarriages. The average female age was 35.4 years. Couples had been attempting to conceive for a mean of 3.2 years. Twenty- two participants (20%) had previously given birth; 24 (22%) had previous intrauterine insemination; and 9 (8%) had previous assisted reproductive technology. The cumulative adjusted proportion of first live births for those completing up to 24 months of NPT treatment was 66 per 100 couples, and the crude proportion was 38%. The cumulative adjusted proportion of first conceptions was 73 per 100 couples, and the crude proportion was 47%. Of the 51 couples who conceived, 12 couples (24%) conceived with CrMS instruction alone, 35 (69%) conceived with CrMS and NPT medical treatment, and 4 (8%) conceived after additional surgical treatment. All births were singleton births; 54% were born at 37 weeks' gestation or later; and 78% had birth weights of 2500 g or greater.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".