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Record W4381486868 · doi:10.1080/2162402x.2023.2222560

Updates on radiotherapy-immunotherapy combinations: Proceedings of 6 <sup>th</sup> annual ImmunoRad conference

2023· review· en· W4381486868 on OpenAlexaff
Fabiana Gregucci, Sheila Spada, Mary Helen Barcellos‐Hoff, Nina Bhardwaj, Charleen Chan Wah Hak, Alba Fiorentino, Chandan Guha, Mónica L. Guzmán, Kevin J. Harrington, Fernanda Herrera, Jamie Honeychurch, Theodore S. Hong, Lorea Iturri, Elisabeth Jaffee, Sana D. Karam, Simon Knott, Constantinos Koumenis, David Lyden, Ariel E. Marciscano, Alan Melcher, Michele Mondini, Anna Mondino, Zachary S. Morris, Sean P. Pitroda, Sergio A. Quezada, Laura Santambrogio, Stephen L. Shiao, John Stagg, Irma Telarović, Robert Timmerman, Marie‐Catherine Vozenin, Ralph R. Weichselbaum, James W. Welsh, Anna Wilkins, Chris Xu, Roberta Zappasodi, Weiping Zou, Alexandre Bobard, Sandra Demaria, Lorenzo Galluzzi, Éric Deutsch, Silvia C. Formenti

Bibliographic record

VenueOncoImmunology · 2023
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsCentre Hospitalier de l’Université de MontréalInstitute of Cancer Research
FundersNational Cancer InstituteUniversity of California, San FranciscoEMD SeronoGenentechEuropean Society for Medical OncologyEli Lilly and CompanyAssociazione Italiana per la Ricerca sul CancroOno PharmaceuticalEisaiNational Institute for Health and Care ResearchSeagenF-star TherapeuticsAccurayMersana TherapeuticsBreak Through CancerRefleXion MedicalRegeneron PharmaceuticalsParker Institute for Cancer ImmunotherapyIpsenVarian Medical SystemsPfizerProstate Cancer FoundationBristol-Myers SquibbAstraZenecaNovocureCancer Research UKBoston Scientific Corporation
KeywordsMedical physicsMedicineRadiation therapyImmunotherapyCancerInternal medicine

Abstract

fetched live from OpenAlex

Focal radiation therapy (RT) has attracted considerable attention as a combinatorial partner for immunotherapy (IT), largely reflecting a well-defined, predictable safety profile and at least some potential for immunostimulation. However, only a few RT-IT combinations have been tested successfully in patients with cancer, highlighting the urgent need for an improved understanding of the interaction between RT and IT in both preclinical and clinical scenarios. Every year since 2016, ImmunoRad gathers experts working at the interface between RT and IT to provide a forum for education and discussion, with the ultimate goal of fostering progress in the field at both preclinical and clinical levels. Here, we summarize the key concepts and findings presented at the Sixth Annual ImmunoRad conference.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient 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 score0.971
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.002
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0030.000
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0020.003

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 head0.037
GPT teacher head0.317
Teacher spread0.279 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations12
Published2023
Admission routes1
Has abstractyes

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