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Record W2619858742 · doi:10.1158/1078-0432.ccr-17-0515

Pediatric Cancer Predisposition Imaging: Focus on Whole-Body MRI

2017· review· en· W2619858742 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

VenueClinical Cancer Research · 2017
Typereview
Languageen
FieldMedicine
TopicRadiation Therapy and Dosimetry
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineMagnetic resonance imagingModalitiesPediatric cancerMedical physicsCancerChildhood cancerRadiologyInternal medicine

Abstract

fetched live from OpenAlex

The American Association for Cancer Research convened a meeting of international pediatric oncologists, geneticists, genetic counselors, and radiologists expert in childhood cancer predisposition syndromes (CPS) in October 2016 to propose consensus surveillance guidelines. Imaging plays a central role in surveillance for most, though not all, syndromes discussed. While encompassing the full gamut of modalities, there is increasing emphasis on use of nonionizing radiation imaging options such as magnetic resonance imaging (MRI) in children and adolescents, especially in the pediatric CPS population. In view of rapid evolution and widespread adoption of whole-body MRI (WBMRI), the purpose of our review is to address WBMRI in detail. We discuss its place in the surveillance of a range of pediatric CPS, the technical and logistical aspects of acquiring and interpreting these studies, and the inherent limitations of WBMRI. We also address issues associated with sedation and use of gadolinium-based contrast agents in MRI in children.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.906
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.004
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 head0.462
GPT teacher head0.645
Teacher spread0.183 · 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