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Record W3038420803 · doi:10.1148/radiol.2020200751

Pediatric Hepatoblastoma, Hepatocellular Carcinoma, and Other Hepatic Neoplasms: Consensus Imaging Recommendations from American College of Radiology Pediatric Liver Reporting and Data System (LI-RADS) Working Group

2020· article· en· W3038420803 on OpenAlexaff
Gary R. Schooler, Judy Squires, Adina Alazraki, Govind B. Chavhan, Victoria Chernyak, Joseph T. Davis, Geetika Khanna, Rajesh Krishnamurthy, Matthew P. Lungren, Prakash Masand, Daniel J. Podberesky, Claude B. Sirlin, Alexander J. Towbin

Bibliographic record

VenueRadiology · 2020
Typearticle
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicineHepatoblastomaHepatocellular carcinomaRadiologyMEDLINETerminologyMedical physicsInternal medicine

Abstract

fetched live from OpenAlex

Appropriate imaging is imperative in evaluating children with a primary hepatic malignancy such as hepatoblastoma or hepatocellular carcinoma. For use in the adult patient population, the American College of Radiology created the Liver Imaging Reporting and Data System (LI-RADS) to provide consistent terminology and to improve imaging interpretation. At present, no similar consensus exists to guide imaging and interpretation of pediatric patients at risk for developing a liver neoplasm or how best to evaluate a pediatric patient with a known liver neoplasm. Therefore, a new Pediatric Working Group within American College of Radiology LI-RADS was created to provide consensus for imaging recommendations and interpretation of pediatric liver neoplasms. The article was drafted based on the most up-to-date existing information as interpreted by imaging experts comprising the Pediatric LI-RADS Working Group. Guidance is provided regarding appropriate imaging modalities and protocols, as well as imaging interpretation and reporting, with the goals to improve imaging quality, to decrease image interpretation errors, to enhance communication with referrers, and to advance patient care. An expanded version of this document that includes broader background information on pediatric hepatocellular carcinoma and rationale for recommendations can be found in Appendix E1 (online).

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.

How this classification was reachedexpand

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.288
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.061
GPT teacher head0.311
Teacher spread0.250 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations81
Published2020
Admission routes1
Has abstractyes

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