Results of surgical excision and evaluation of factors associated with survival time in dogs with lingual neoplasia: 97 cases (1995–2008)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To describe the clinical characteristics, treatments, outcomes, and factors associated with survival time in a cohort of dogs with lingual neoplasia that underwent surgical excision. DESIGN: Retrospective case series. Animals-97 client-owned dogs. PROCEDURES: Medical records of dogs with a lingual tumor examined between 1995 and 2008 were reviewed. Records were included if a lingual tumor was confirmed by histologic examination and surgical excision of the mass was attempted. Data were recorded and analyzed to identify prognostic factors. RESULTS: Clinical signs were mostly related to the oral cavity. For 93 dogs, marginal excision, subtotal glossectomy, and near-total glossectomy were performed in 35 (38%), 55 (59%), and 3 (3%), respectively. Surgery-related complications were rare, but 27 (28%) dogs had tumor recurrence. The most common histopathologic diagnoses for the 97 dogs were squamous cell carcinoma (31 [32%]) and malignant melanoma (29 [30%]). Eighteen (19%) dogs developed metastatic disease, and the overall median survival time was 483 days. Median survival time was 216 days for dogs with squamous cell carcinoma and 241 days for dogs with malignant melanoma. Dogs with lingual tumors ≥ 2 cm in diameter at diagnosis had a significantly shorter survival time than did dogs with tumors < 2 cm. CONCLUSIONS AND CLINICAL RELEVANCE: Similar to previous studies, results indicated that lingual tumors are most commonly malignant, and squamous cell carcinoma and malignant melanoma predominate. A thorough physical examination to identify lingual tumors at an early stage and surgical treatment after tumor identification are recommended because tumor size significantly affected survival time.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it