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Record W2039315062 · doi:10.1007/s13244-013-0294-0

Solid malignant retroperitoneal masses—a pictorial review

2013· article· en· W2039315062 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

VenueInsights into Imaging · 2013
Typearticle
Languageen
FieldMedicine
TopicSoft tissue tumor case studies
Canadian institutionsToronto General HospitalWomen's College HospitalUniversity of TorontoUniversity Health NetworkMount Sinai Hospital
Fundersnot available
KeywordsMedicineNeuroradiologyRadiologyMagnetic resonance imagingUltrasoundInterventional radiologyBiopsyComputed tomographyNeurology

Abstract

fetched live from OpenAlex

Primary retroperitoneal masses are a rare but important group of neoplasms. Cross-sectional imaging has revolutionised the investigation of patients with retroperitoneal neoplasms. Both computed tomography (CT) and magnetic resonance imaging (MRI) can contribute to tumour diagnosis, though histological confirmation is often required because of the considerable overlap of imaging features. Cross-sectional imaging is key to the pre-operative staging and planning of retroperitoneal masses, though ultrasound may also help in certain instances. Imaging also helps to select and guide the site to biopsy from these usually large and heterogeneous neoplasms. This article aims to review many of the primary retroperitoneal neoplasms that may be encountered by the radiologist.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.578
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.016
GPT teacher head0.317
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