Lingual Frenulum Protocol with scores for infants
Bibliographic record
Abstract
An experimental protocol model for frenulum evaluation was first designed, and administered to ten infants in 2010. After obtaining the data and statistical analysis, the protocol was re-designed and administered to 100 infants. The aim of this study is to present an efficient and effective lingual frenulum protocol with scores for infants. From the experimental protocol model, a new protocol was designed. One speech-language pathologist, and specialist in orofacial myology, administered the new protocol to 100 full-term infants. All steps of the protocol were recorded and photographed. The data collected was sent to two specialists in the area, who evaluated the cases based on the recordings and photographs. The data from the three evaluations were compared. A two-part protocol was designed to evaluate the lingual frenulum in infants. The first part consists of clinical history with specific questions about family history and breastfeeding. The second part consists of clinical examination: anatomo-functional, non-nutritive and nutritive sucking evaluations. A new lingual frenulum protocol with scores for infants was designed, and has proved to be an effective tool for health professionals to assess and diagnose anatomical alterations of the lingual frenulum, and its possible interference with breastfeeding.
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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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".