Clinical prognostic factors in canine histiocytic sarcoma
Bibliographic record
Abstract
Canine histiocytic sarcoma (HS) is an aggressive neoplasia with variable clinical course and fatal outcome. The goals of this study were to evaluate a large cohort of canine patients with immunohistochemically confirmed HS and identify clinical prognostic factors. Biopsy submissions to the Michigan State University with tentative HS diagnoses were histologically and immunohistochemically confirmed, medical records collected, and interviews with relevant veterinary clinics conducted. Of 1391 histopathology submissions with a diagnosis containing the word 'histiocytic', 335 were suspicious for malignancy, and 180 were consistent with HS and had adequate clinical information recorded. The most commonly represented breeds were Bernese mountain dogs (n = 53), labrador retrievers (n = 26) and golden retrievers (n = 17). Median survival for all dogs in the study was 170 days, and subgroup analysis identified palliative treatment, disseminated HS, and concurrent use of corticosteroids as statistically significant negative factors for survival, in both uni- and multi-variate methodologies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".