Bibliographic record
Abstract
Objective To understand the epidemic regulation of mycoplasmal pneumonia in Beijing and the carriageable time of mycoplasma pneumonia (MP) after affecting mycoplasmal pneumonia.Methods The data of 1929 inpatients with mycoplasmal pneumonia in the department of pediatrics were statisted. And the incidences in different quarters, ages and years were analyzed. Twenty patients with mycoplasmal pneumonia were treated.Results There were no difference of discrepancy in the first quarter, the second and the third,all P0.05. The first quarter, the second, the third respectively compared with the fourth, all P0.05. Six to nine years old compared with 9-14 years old, P0.05. One month to 3 years old compared with 4-6 years old, 7-9 years old, 10-14 years old, all P0.05.Four to six years old compared with 7-9 years old, 10-14 years old, P0.05.The incidence declined gradually in 1992-1994. The incidence was the highest in 1995. The shortest carriageabe time of MP was a half month.The average carriageabe time of MP was one and half months. The longest carriageabe time of MP was four and half months. Conclusions The incidence of MP was closely related to season,age and year.The carriageabe time of MP after the onset differed with different patients,and the correlation factors should be further studied.
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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 | 0.000 | 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".