The use of a tongue tie alters laryngohyoid position in the standing horse
Bibliographic record
Abstract
REASONS FOR PERFORMING STUDY: The use of tongue ties in racing is common, yet there are few data to support their efficacy. In order to make appropriate recommendations for clinical practice and policy on tongue ties, data documenting their effect on upper airway structure are necessary. OBJECTIVES: To determine the effect of a tongue tie on the resting laryngohyoid position of the standing horse. STUDY DESIGN: Experimental study. METHODS: Twelve normal Standardbred horses were subjected to ultrasonographic measures of laryngohyoid position during 3 phases of tack application: Phase I--halter and lead; Phase II--bit, bridle, harness and check applied; and Phase III--as in Phase II but with the tongue tie added. RESULTS: Compared to Phase I, during Phase III with the application of a tongue tie a significant difference between lingual process position was noted both rostrally and caudally (P<0.001 and P<0.001), such that the tongue tie resulted in an increase in lingual process depth. The tongue tie in Phase III resulted in a decrease in depth of the thyroid cartilage and basihyoid bone compared to the Phase I location (P = 0.007 and P = 0.0047). CONCLUSION: The use of a tongue tie has a significant effect on the basihyoid and thyroid cartilage positions in the standing horse. POTENTIAL RELEVANCE: This is the first report documenting a difference in laryngohyoid morphology following the application of a tongue tie, providing evidence that the use of a tongue tie has a measurable effect on upper airway structure. The functional implications of this finding are yet to be elucidated.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".