Управленческие инструменты деятельности центров содействия занятости выпускников
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
Recently the Korean Neonatal Network (KNN) was established in order to enhance treatment outcomes further through the registration of very-low-birth-weight infants (VLBWI) data. The present study was conducted on 2,606 VLBWI, 2,386 registered and 220 un-registered, in the KNN participating centers, with the objective of reporting on recent survival rates of VLBWI in Korea and verifying the changing trends in survival rates with data from the 1960s and beyond. The study also aimed to compare the premature infants' survival rate in Korea with those reported in neonatal networks of other countries. The recent survival rate of VLBWI increased more than twice from 35.6% in the 1960s to 84.8%, and the survival rate of the extremely low birth weight infants (ELBWI) increased by more than 10 times, indicating improvement of the survival rate in premature infants with lower birth weight and gestational age. Comparison of VLBWI between countries showed improved survival rates according to each birth weight group in Canada, Australia-New Zealand, and European countries with Japan at the head, but in terms of comparison based on gestational age, differences, except for Japan, have been reduced. Efforts to increase the survival rate of premature infants in Korea with low birth rate are inevitable, and they should be the foundation of academic and clinical development based on its network with advanced countries.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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