Cervical length as a predictor of pre–term birth in twin gestations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The aim of this study was to determine the predictive value of cervical length as a risk factor for spontaneous pre-term birth in twin gestations. A retrospective chart review was carried out on patients with twin pregnancies referred to our multiples' clinic. Cervical length was measured by transvaginal ultrasonography. Patients with an indicated pre-term delivery or intervention were excluded from the analysis. Outcomes included preterm delivery < 28 and < 35 weeks gestation. After extracting the data, 2 x 4 tables were constructed. Likelihood ratios were then generated for cervical lengths < or = 2.0 cm, < or = 2.5 cm, < or = 3.0 cm, and > 3.0 cm. Because of the limited number of measurements taken < 25 weeks gestation, we elected to collapse the tables, thereby achieving more meaningful results. For measurements taken before 30 weeks gestation, a shorter cervix did predict delivery < 28 weeks gestation (likelihood ratios for cervical lengths < or = 2.0 cm, < or = 2.5 cm, < or = 3.0 cm, and > 3.0 cm were 4.43, 1.94, 0.97, and 1.02, respectively). The probability of preterm delivery < 35 weeks gestation increased with decreasing cervical length (likelihood ratios for cervical length < or = 2.0 cm, < or = 2.5 cm, < or = 3.0 cm, and > 3.0 cm were 2.58, 1.66, 1.38, and 0.81, respectively). A shorter cervix measured before 30 weeks gestation was a stronger predictor of preterm delivery < 28 weeks compared to < 35 weeks gestation. Cervical length was not predictive of preterm delivery if measured after 30 weeks. Cervical length is predictive of preterm delivery < 28 weeks and < 35 weeks gestation when measured before 30 weeks gestation. No trend was seen when measured after 30 weeks gestation. A prospective study is currently underway to confirm these results.
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.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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 it