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Record W4415740840 · doi:10.1007/s00330-025-12045-7

Correction: Imaging in staging, treatment planning, and monitoring of hepatocellular carcinoma for local and locoregional therapies: consensus recommendations from EORTC and ESGAR

2025· erratum· en· W4415740840 on OpenAlexaff
Osman Öcal, Christoph J. Zech, Maria Antonietta Bali, David Pasquier, Felix M. Mottaghy, Ingo Einspieler, Nikolaos Kartalis, Irene Bargellini, Roberto Iezzi, Timm Denecke, Wolfgang G. Kunz, Bernhard Gebauer, Henning Wege, Roberto Cannella, Daniela E. Oprea‐Lager, Arndt Vogel, Bruno Sangro, Max Seidensticker, Francesca De Felice, Serena Pisoni, Hossein Hemmatazad, Kerstin Schütte, Joost J.C. Verhoeff, Bora Peynırcıoğlu, Cesare Guida, Maxime Dewulf, Christophe M. Deroose, Valeria Dionisi, John Ramage, Marino Venerito, Mark C. Burgmans, Carolina de la Pinta, Huw Roach, Serdar Aslan, Stefano Cappio, Christian Stroszczynski, Uli Fehrenbach, Lorenza Rimassa, Lukas Luerken

Bibliographic record

VenueEuropean Radiology · 2025
Typeerratum
Languageen
FieldMedicine
TopicHepatocellular Carcinoma Treatment and Prognosis
Canadian institutionsPrincess Margaret Cancer CentreToronto General Hospital
Fundersnot available
KeywordsInterventional radiologyHepatocellular carcinomaNeuroradiologyStatement (logic)MEDLINE

Abstract

fetched live from OpenAlex

https://doi.org/10.1007/s00330-025-11699-7 published online 23 May 2025. In the original article, affiliation of study group member Lorenza Rimassa’s affiliation was incorrectly given as IRCCS Humanitas Research Hospital, Roma, Italy. The correct affiliation is Humanitas Cancer Center, IRCCS Humanitas Research Hospital, Rozzano (Milan), Italy. Lorenza Rimassa is also affiliated with Department of Biomedical Sciences, Humanitas University, Pieve Emanuele (Milan), Italy, which was left out in the original article. Furthermore, the following Conflict of interest statement was missing in the original article: L.R. has received consulting fees from AbbVie, AstraZeneca, Basilea, Bayer, BMS, Elevar Therapeutics, Exelixis, Genenta, Hengrui, Incyte, Ipsen, Jazz Pharmaceuticals, MSD, Nerviano Medical Sciences, Roche, Servier, Taiho Oncology, Zymeworks; lecture fees from AstraZeneca, Bayer, BMS, Eisai, Guerbet, Incyte, Ipsen, Roche, Servier; travel expenses from AstraZeneca, Servier; and institutional research funding from AbbVie, AstraZeneca, BeiGene, Exelixis, Fibrogen, Incyte, Ipsen, Jazz Pharmaceuticals, MSD, Nerviano Medical Sciences, Roche, Servier, Taiho Oncology, TransThera Sciences, Zymeworks. The original article has been corrected.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.294
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)0.0000.000

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 head0.051
GPT teacher head0.279
Teacher spread0.228 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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