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Record W2124350427 · doi:10.1148/rg.264055144

Evaluation of Bowel and Mesenteric Blunt Trauma with Multidetector CT

2006· review· en· W2124350427 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRadiographics · 2006
Typereview
Languageen
FieldMedicine
TopicAbdominal Trauma and Injuries
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineBluntRadiologyAbdominal traumaLaparotomyMesenteric VeinMesenterySurgery

Abstract

fetched live from OpenAlex

Bowel and mesenteric injuries are detected in 5% of blunt abdominal trauma patients at laparotomy. Computed tomography (CT) has been shown to be accurate for the diagnosis of bowel and mesenteric injuries and is the diagnostic test of choice in the evaluation of blunt abdominal trauma in hemodynamically stable patients. Specific CT findings of bowel and mesenteric injuries include bowel wall defect, intraperitoneal and mesenteric air, intraperitoneal extraluminal contrast material, extravasation of contrast material from mesenteric vessels, and evidence of bowel infarct. Specific signs of mesenteric injury are vascular beading and abrupt termination of mesenteric vessels. Less specific signs of bowel and mesenteric injuries include focal bowel wall thickening, mesenteric fat stranding with focal fluid and hematoma, and intraperitoneal or retroperitoneal fluid. When only nonspecific signs of bowel and mesenteric injuries are seen on CT images, correlation of CT features with clinical findings is necessary. A repeat CT examination after 6-8 hours if the patient's condition is stable may help determine the significance of these nonspecific findings.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.985
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.076
GPT teacher head0.370
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it