Bacterial, behavioral and environmental factors associated with early childhood caries
Bibliographic record
Abstract
The goals of this cross-sectional study were to characterize and compare demographic, behavioral, and environmental factors potentially associated with early childhood caries (ECC) and to assess salivary levels of mutans streptococci (MS) and lactobacilli (LB) in underserved, predominantly Hispanic children. One hundred forty-six children aged 3 to 55 months with a range of caries experience were identified and examined. ECC was primarily associated with the presence of MS and lack of access to dental care. Salivary MS levels among young children with ECC were higher than would be expected in a dentally healthy population, but lower than levels reported among older children at high risk for caries. After adjustment for age, children with log10 MS > or = 3.0 or log10 LB > or = 1.5 were about five times as likely (OR=4.9, 95% CI=2.0, 12.0) to have ECC than those with lower bacterial levels. This study demonstrated a significant association between relatively low cariogenic bacterial levels and dental caries in infants and toddlers. Antibiotic use, exposure to lead, and anemia were not significantly associated with the number of decayed and filled surfaces or decayed and filled teeth. ECC correlated significantly with child's age and lack of dental insurance of the children, as well as inversely with both family income and the educational level of the mother of the child.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".