Cutaneous neoplastic lesions of equids in the central United States and Canada: 3,351 biopsy specimens from 3,272 equids (2000–2010)
Bibliographic record
Abstract
OBJECTIVE: To identify epidemiological trends in cutaneous neoplasms affecting equids in central North America and compare them with previously reported trends. DESIGN: Retrospective case series. SAMPLE: 3,351 cutaneous biopsy specimens from 3,272 equids with a neoplastic diagnosis. PROCEDURES: Diagnostic reports from 2 diagnostic laboratories (Colorado State University and Prairie Diagnostic Services Inc) were reviewed for frequency of specific lesions and epidemiological trends. Variables included in analyses (if known) were age, sex, breed, geographic location, date of diagnosis, location of neoplasm on the body, and presence or absence of ulceration. RESULTS: Sarcoid, squamous cell carcinoma (SCC), and melanoma were the 3 most common tumors diagnosed. Tumors associated with UV radiation (SCC, SCC in situ, hemangioma, hemangiosarcoma) were 2.3 (95% confidence interval [CI], 1.8 to 3.0) times as common in biopsy specimens received by Colorado State University than in specimens received by Prairie Diagnostic Services Inc. Appaloosa horses and American Paint horses, respectively, were 7.2 (95% CI, 5.6 to 9.2) and 4.4 (95% CI, 3.6 to 5.4) times as likely as other breeds to have tumors associated with UV radiation. Thoroughbreds were predisposed to cutaneous lymphoma, whereas Arabians were more likely to have melanomas. Draft and pony breeds were 3.1 (95% CI, 1.9 to 5.1) times as likely as other breeds to have benign soft tissue tumors. Morgans and pony breeds more commonly had basal cell tumors. Tumors in the perianal region were significantly more likely to be SCC or melanoma while tumors on the limbs were more likely to be giant cell tumor of soft parts. CONCLUSIONS AND CLINICAL RELEVANCE: Signalment, anatomic location of the mass, and geographic location of the horse can be used to help equine practitioners formulate differential diagnoses for cutaneous masses. Further research is necessary to identify the biological basis for the development of many equine cutaneous neoplasms.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".