Učestalost rađanja dece sa kongenitalnim anomalijama u porodilištu Prokuplje
Bibliographic record
Abstract
Congenital defects assume morfological, structural and functional abnormality of organs, organic systems and tissue, formed during morphogenesa present and visible at birth. Etiological factors which lead to forming point of congenital defects could be: multifactorial, monogenetic, chromozomic teratogenic and unknown causes. The aim of our work is find the birth of children frequency with congenital defects in the maternity hospital in Prokuplje during the period of time from 1990. to 2004. The details are taken from the data base of live born children. Out of 16479 newborn infants observed in a 15 year period of time, 659 or 4% had some of the congenital defects. The most frequent congenital defects appeared on their feet and hips. Birth of children is obvious with Sy Down. Such observation fits in the world's percentage as much as in our country. It's worrying situation that the birth rate had gone down during this period of time for an quarter and number of children with congenital defects had gone up.
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.
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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".