Morphology of the Occlusal Surfaces of Premolar and Molar Teeth as an Indicator of Age in the Horse
Bibliographic record
Abstract
The purpose of this study was to investigate the use of cheek tooth occlusal surface morphology as an indicator of age in the horse using a blinded cross-sectional design. Twenty horses of varying age, breed and sex were used. Horses of known age (foaling date) were euthanized for reasons other than dental disease. Following disarticulation of the head and sectioning of the mandibles, cheek teeth were cleaned using running water and photographs were taken of each arcade. Using a computer-based program, the total surface area of each premolar and molar, the outer enamel ridge perimeter distance, infundibular surface areas and perimeter distances were measured. Further anatomical data were calculated from these measurements and a statistical analysis of the relationship between horse age and cheek tooth occlusal morphology was performed. Results indicated that multiple anatomical regions within the occlusal surface of the equine cheek tooth can be used as an indicator of age. There are important differences between mandibular and maxillary teeth as well as between teeth in the same dental arcade. Horse size is also of significance. The mesial infundibular surface area as a percentage of the total surface area of tooth 111, and the mesiodistal length of 1/2/3/4 09 teeth, most closely approximates age within our mathematical model. Cheek tooth morphological data can be used to predict age in horses that possess all their permanent dentition. In cases in which the age of horses cannot be accurately determined from incisor examination, cheek teeth may be used.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".