Retrospective analysis on the measurement results of antibodies against Mycoplasma pneumoniae in infants and children
Bibliographic record
Abstract
Objective To procure the seroepidemiologic of mycoplasma pneumoniae infection.Methods Passive particle agglutination assay was used to detect serum antibodies against mycoplasma pneumoniae in infants and children who went to see a doctor in years between 2010and 2012.The seroepidemiologic dates was analyzed,including positive rates in whole subjects,in male or female groups,in different seasons or age groups as well as different clinical diagnosis.Results In 14 037serum samples,2 431(17.3%)had positive results;The positive rate in female was 20.0%(1 156/5 782),higher than 15.4%(1275/8 255)in male(χ2=49.116,P0.05);The positive rate in 6-14years old was 24.6%(1 687/6 849),which was the highest,and then that in 3-5years old was 15.0%(325/2 161),in 1-2years old was 12.6%(286/2 277),and in 25days old to 1year old was 4.8%(133/2 750),which was the lowest.The positive rate in the fourth quarter was 20.6%(677/3 287),and that of the third quarter was 19.3%(670/3 475),of the first quarter was 18.5%(646/3 492),and of the second quarter was 11.6%(438/3 783).The peak season was different in the four different age-groups.The highest positive rate in different clinical diagnosis was bronchopneumonia-group with 24.3%(1 272/5 227),and the lowest was herpangina-group with 8.8%(84/956).Conclusion Mycoplasma pneumoniae positive rate measured by the antibodies in serum of female children is higher than that of male children,and the positive rate will be higher and higher with children growing.The peak season is different in various years-old children.The positive rate of antibodies against Mycoplasma pneumoniae is highest in the children who are diagnosed as bronchopneumonia.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".