Comparison of Caries Occurence Between Resin Based and Glass Ionomer Based Pit and Fissure Sealants in Young Permanent Molars After One Year Application
Bibliographic record
Abstract
The use of anatomic grooves or pits and fissures on the occlusal top of permanent grinders retains food scraps and increases the formation of caries. Inserting and fastening these exposed regions with pit-and fissure sealants has the potential to avert the occurrence of these injuries in teeth. The tools used for such process have the shape of a resin based and a glass ionomer cement (referred to as GIC hereafter). This study aims to compare white spot index (ICDAS) after applying resin based and fissure sealant glass ionomer, and to determine the more efficient types of material over a long period of time method. This study uses experimental pre-test and post-test methods. The research population consists of grade I, II, and III elementary students from the Elementary School No.2, Central Cupak, Padang. Samples were obtained through purposive sampling. The research involves 2 types of sample each of which consists of 30 children who were given resin based sealant application as well as glass Ionomer. ICDAS-II index was used to assess white spot index following one year application. The research data was analyzed with SPSS Statistics through unpaired t-test. The result shows that there is no major distinction between resin based sealant application and glass ionomer cement following one year application(p = 0,23). This study concludes that resin based sealants and glass ionomer cement constitute valuable pit and fissure sealant materials. The reaction of these materials must be evaluated over a longer period to determine the mean retention period and to confirm if a new application is needed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".