Hubungan Pengetahuan Ibu Tentang Pertumbuhan Gigi dengan Kasus Persistensi pada Anak Usia 7-11 Tahun di Wilayah Kerja Puskesmas Andalas
Bibliographic record
Abstract
Objective: Over-retained tooth is condition when the primary tooth as retainer of the permanent tooth not exfoliate promptly, while permanent tooth has been erupted. The oral health problems in Padang reported anomalies of tooth development and eruption were in the second place with 8.897 cases in 2018. Andalas Public Health Center (PHC) possessed the highest number of over-retained tooth cases which becomes their primary problem in this category. Children's oral and dental health particularly over-retained tooth is largely determined by the awareness of their mothers’ behaviour and knowledge. The purpose of this study was to determine the correlation between mothers’ knowledge towards dentition and over-retained tooth during mixed dentition case on children aged 7-11 years in Andalas PHC area. Method: This study was analytical observation research with cross sectional design. There were 106 samples of children aged 7-11 years together with their mothers in Andalas PHC obtained by using simple random sampling. Data were collected through questionnaire and children's oral examination. Data were analyzed by the Chi-Square test. The results of this study showed that 54.7% of children in Andalas PHC area had over-retained tooth. The high level of mother's knowledge about dentition was 55.7% Result: The results of the analysis between the mother's knowledge of dentition and over-retained tooth obtained value of p = 0,0001. Conlusion: There was a significant correlation between mothers knowledge of dentition and occurrence of over-retained tooth among children aged 7-11 years in Andalas PHC area.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.008 | 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".