MétaCan
Menu
Back to cohort
Record W3013948509 · doi:10.5152/dir.2019.19391

Abdominal and pelvic radiographs of medical devices and materials- part 2: neurologic and genitourinary devices and materials

2020· review· en· W3013948509 on OpenAlex
Rishi Philip Mathew, Medica Sam, Timothy Alexander, Vimal Patel, Gavin Low

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

VenueDiagnostic and Interventional Radiology · 2020
Typereview
Languageen
FieldMedicine
TopicPelvic and Acetabular Injuries
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicinePelvisAbdomenRadiographyRadiologyGenitourinary systemMedical physicsConfusionAnatomy

Abstract

fetched live from OpenAlex

Radiographs of the abdomen and pelvis are routinely obtained as a standard part of clinical care for the abdomen and pelvis. Brisk advances in technology over the last few decades have resulted in a multitude of medical devices and materials. Recognizing and evaluating these devices on abdominal and pelvic radiographs are critical, yet increasingly a difficult endeavor. In addition, multiple devices serving different purposes may have a similar radiographic appearance and position causing confusion for the interpreting radiologist. The role of the radiologist is to not only identify accurately these medical objects, but also to confirm for their accurate placement and to recognize any complications that could affect patient care, management or even be potentially life threatening. An extensive online search of literature showed our review article to be the most comprehensive work on medical devices and materials of the abdomen and pelvis, and in this second part of our two-part series, we discuss in depth about the neurologic and genitourinary devices seen on abdominal and pelvic radiographs.

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)0.001
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 score0.804
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.031
GPT teacher head0.333
Teacher spread0.302 · 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