Analysis on inspection result for perinatal infant lacuna in yunnan province from 1999 to 2003.
Bibliographic record
Abstract
Objactive: To find out the occurring types and distributing area of perinatal infant lacuna in Yunnan Province, and searching the related factors, which affect to the natal lacuna. Methods: From January 1999～December 2003, we had inspected the perinatal infants will delivery in 28 weeks till to their natal date after 7 days in any Provincial and Municipal hospitals. According to the National unified natal lacuna, we reported the Infant Quarter's Report Natal Lacuna Registry Card in every quarter to Provincial Health Center for Women and Children. Results: The ratio of perinatal infants with natal lacuna was 10.26‰. (1013/98690), thereinto, the deformity finger (toe), split lip and deformity neural canal are the highest frequency three kinds in Yunnan Provincial Perinatal infants with natal lacuna. The ratio of masculine natal lacuna is 1,084.4‰ (561/51732), it is higher than female of 941.3‰ (442/46958). And 1078.9‰ (630/58391) in city is higher than 950.4‰ (383/40299) in countryside. The maternity age ≥35 is the important reason of natal lacuna.Conclusion: We must organize the educational activities and medical check for antemarital genital health, guidance newlywed pick at the folic acid for preventive the deformity neural canal. Strengthen on civil health education, promoting the environmental consciousness, protect the antemarital health, health protection in prepotency and pregnant confinement, organize the prenatal examination and diagnose are the effective measures to decrease the natal lacuna.
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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 | 0.002 | 0.002 |
| 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) | 0.001 | 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".