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
Computed tomography (CT) can provide essential anatomic and physiologic information required to determine management of intraabdominal and retroperitoneal injuries sustained during blunt abdominal trauma. It can help in evaluation of the type and severity of parenchymal injury, the extent of perirenal hemorrhage and parenchymal devascularization, and the presence of urinary extravasation. CT can help confirm the presence of major injuries to the vascular pedicle and depict occult renal pathologic conditions. Principal indications for the use of CT in the evaluation of blunt renal trauma include (a) the presence of gross hematuria, (b) microscopic hematuria associated with shock (systolic blood pressure <90 mm Hg), and (c) microscopic hematuria associated with a positive result of diagnostic peritoneal lavage. The majority of renal injuries sustained during blunt abdominal trauma are contusions and minor parenchymal lacerations amenable to nonoperative management. Deep parenchymal lacerations, urinary extravasation, and mild to moderate degrees of parenchymal devascularization may also be treated conservatively. Radiologists should look for coexisting renal lesions such as tumors and traumatic false aneurysms that may alter management.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| 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