Bibliographic record
Abstract
According to a report concerning the antenatal corticosteroid (ACS) administration rate among eligible patients who delivered from 24 34 weeks of gestation at a tertiary center in the United States in 2014, 81.3% of them received at least 1 dose of ACS [1]. This rate may be higher than the average ACS administration rate in Japan (about 51% in 2011) [2]. For example, in my institution, one of the major perinatal centers in Tokyo, Japan, only 60 in 135 patients (44%) who delivered from 24 32 weeks of gestation received at least 1 dose of ACS in 2008 2010. The difference in the ACS administration rates between Japan and the United States may be due to the differences in the perinatal care system. In Japan, about half of all pregnancies and deliveries are managed at private clinics without neonatologists; patients with a risk of preterm birth managed at private clinics need to be transported to perinatal centers. There may be some cases of delayed transport leading to a decreased time period for ACS administration at perinatal centers. In my institution, the ACS administration rate (27%: 21 in 79 cases) in cases following transport from private clinics was significantly lower than that in those managed in-house (70%: 39 in 56 cases, odds ratio 0.16, 95% confidence interval 0.07 0.34, P < 0.01 by the Chi-square test). Therefore, in Japan the early transport of patients at risk of preterm delivery from private clinics to perinatal centers may improve the ACS administration rate.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.004 | 0.001 |
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".