Pacifier Sizing as a Prescription for Better Oral Health Outcomes for Infants: A Call to Action
Bibliographic record
Abstract
Sucking is essential for feeding and impacts the development of the cranio-facial-respiratory complex (CFRC). Non-nutritive sucking on a pacifier causes palatal narrowing and modifies the natural balanced relationship between intraoral pressure, peristaltic action of the tongue and the palate. Advanced engineering models have shown that malocclusions caused by pacifier use, are often a result of improper sizing. The sizing of pacifiers has historically been based on chronological age. Chronological age is not a size metric. Undersized pacifiers in a baby’s mouth can cause growth complications, palatal collapse airway incompetence and other orthodontic problems that can last a lifetime. Technical advances in facial anthropometrics and predictability of the rapid growth of the infant palate, can guide recommendations for pacifier size and design. This encourages change to a model of biometric sizing. Smartphone applications are being developed that use Ai and machine learning can predict conformity between palatal width and pacifier width.
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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 | 0.016 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.012 | 0.024 |
| Insufficient payload (model declined to judge) | 0.020 | 0.007 |
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".