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
CASE DESCRIPTION: A nearly 6-year-old female spayed Labrador Retriever was presented for acute abdominal pain and lethargy. The dog had no previous health concerns apart from occasional episodes of urinary incontinence in the 2 months prior to presentation. A retroperitoneal mass involving the right ureter was found during the investigations. Serum urea was mildly elevated, but the serum creatinine was within the normal range. No distant metastases were detected. A right ureteronephrectomy was performed. The ureteral mass was confirmed as a leiomyosarcoma and completely excised. The kidney was histologically normal. Unfortunately, during a routine 3-month postoperative assessment, a recurrent mass at the previous retroperitoneal surgical site was confirmed by biopsy to be a leiomyosarcoma. Courses of doxorubicin and chlorambucil were given, but failed to halt the progression of the recurrent mass. The dog was euthanised 5.5 months postoperatively because of poor quality of life. CLINICAL RELEVANCE: Ureteral leiomyosarcoma should be on the differential diagnosis list for a retroperitoneal mass, possibly causing severe abdominal pain with minor clinical signs associated with the urinary tract. This dog in this reported case of ureteral leiomyosarcoma had a short survival time, despite complete surgical excision and chemotherapy, because of local recurrence.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it