HUBUNGAN ANTARA HYGIENE GIGI DENGAN KEJADIAN PNEUMONIA PADA BALITA UMUR 36-59 BULAN DI PUSKESMAS KLIRONG II
Bibliographic record
Abstract
The pneumonia is health problem in world because the death level pneumonia desease hight, not only in proceed country but also in modern countries such as Amerca Serikat, Canada dan Eropa country. Some factors of risk pneumonia for example age, weather or climate, bad toht hygiene act. The purpose of this research is to know sum of children under five years old that suffering pneumonia, to know the sum of child pneumonia that bad tooht hygiene. Case Control with the approach of Retrospektive sampling . Populatian of the child 36-59 moth that suffering pneumonia in manistran Center the society Healt of Klirong II of 32 person . Analys the date with the analisys of is non parametrical statistic that is Spearman rho correlatian analys. Instrumen used check list observ of condition tooht hygiene on child under five years old. Sum of pneumonia child that bad tooht hygiene are 17 person. The result of date analys using Spearman rho test with statistic technique is P value 0,024, show that there are correlation betwen bad tooth hygiene and occurance pneumonia in children under five tears old. Information about pneumonia is needed to mother child that suffering pneumonia to decrease occurance pneumonia in child under five years old. Keywords: Bad tooht hygiene, Occurance pneumonia, The child under five years old.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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".