Incisor tooth breakage, enamel defects, and periodontitis in a declining Alaskan moose population.
Bibliographic record
Abstract
We examined 56 anterior segments of mandibles from moose harvested from a declining population that was affected by tooth wear and breakage at higher rates than in moose elsewhere on the Seward Peninsula, Alaska. Incisor teeth were examined for extent of tooth wear and breakage, the degree and prevalence of surface enamel defects, and radiographic evidence of periodontitis. Body size (incisor arcade width of adult moose) and body condition index (timing of tooth eruption in yearlings) of the Seward Peninsula population were compared to other Alaskan moose populations. Mean (± SE) age of adult moose in the study was 4.6 ± 0.4 years. The age distribution of harvested moose was 32% yearling, 61% young adult (2-6 years old), 4% prime adult (7-11 years old), and 4% old moose �!����\HDUVROG����&RPSDUDWLYHO\�VPDOOHUERG\�VL)HLQPRRVHREV HUYHGLQWKLVVWXG\�SUREDEO\�UH?HFWV� the absence of older animals in the 2002 harvest. Timing of tooth eruption in yearlings was within the range of other moose populations. Mean tooth wear and breakage score was 2.1 ± 0.2. Ninety-three percent of the teeth exhibited hypoplastic enamel defects (pits) and staining, while 59% exhibited vertical and horizontal fracture lines on both labial and lingual tooth surfaces. Fifty-three percent of examined teeth showed radiographic signs consistent with periodontitis. Evidence of osteoporosis was present in 74% of the examined jaws. We hypothesize that observed enamel defects exacerbate age-related tooth wear and breakage in this population thereby resulting in accelerated demise of older animals. The skewed age distribution, with very few animals > 7 years supports this conclusion. The etiology of the observed enamel defects is unclear and requires further investigation. ALCES VOL. 42: 65-74 (2006)
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".