Detection of Children Anti-Streptolysin “O”of Our Hospital in 2013
Bibliographic record
Abstract
Objective: To explore the ASO positive rates in different ages,genders and quarters in children,take the effective prevention of infectious disease interrelated with streptococcus. Methods: There were 4,052 children with ASO detected from pediatrics department of our hospital in 2013. Then a statistical analysis about the test results of ASO in different ages,genders and quarters was made by particles enhance transmission immunoturbidimentry assay. Results: Among the 4,052 children with ASO detected,the positive rate was 17.18%. The positive rate of ASO in male and female were 19. 76% and 13. 47%,respectively,and there was a significant difference between different genders of children( P<0.01). The positive rate of ASO in children of 0 ~ 3 age,4 ~ 6 age,7 ~ 9 age,10 ~12 age and 13 ~ 15 age were accounting for 0. 47%,7. 94%,33. 80%,42. 02% and 30. 67%,respectively,there were significant differences among different age stages of children( P<0.01). The positive rate of ASO in the first quarter,the second quarter,the third quarter and the fourth quarter were accounting for 19.37%,16.69%,14.14%,18.84%,respectively,there were significant differences among different quarters( P< 0. 01). Conclusion: Streptococcal infection is common in the school-age children,and rare in infants.Streptococcal infection rate is higher in boys than girls,and is more likely to occur in winter and spring.
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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 | 0.001 | 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) | 0.002 | 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".