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Record W4402966386 · doi:10.1016/s1470-2045(24)00407-8

Radiotherapy and theranostics: a Lancet Oncology Commission

2024· review· en· W4402966386 on OpenAlexaff
May Abdel–Wahab, Francesco Giammarile, M. Carrara, Diana Páez, Hedvig Hricak, Nayyereh Ayati, Jing Jing Li, Malina Mueller, Ajay Aggarwal, Akram Al‐Ibraheem, Sondos A. Al-Khatib, Rifat Atun, Daniel Berger, Roberto C. Delgado Bolton, John M. Buatti, Graeme Burt, Olivera Ciraj‐Bjelac, Lisbeth Cordero-Mendez, Manjit Dosanjh, Thomas Eichler, Elena Fidarova, Soehartati Gondhowiardjo, Mary Gospodarowicz, Surbhi Grover, Varsha Hande, Ekaterina Harsdorf-Enderndorf, Ken Herrmann, Michael S. Hofman, Ola Holmberg, David A. Jaffray, Peter Knoll, Jolanta Kunikowska, Jason S. Lewis, Yolande Lievens, Miriam Mikhail-Lette, Dennis A. Ostwald, Jatinder Palta, Platon Peristeris, Arthur Accioly Rosa, Soha Ahmed Salem, Marcos Augusto dos Santos, Mike Sathekge, Shyam Kishore Shrivastava, Egor Titovich, Jean-Luc Urbain, Verna Vanderpuye, Richard L. Wahl, Jennifer S. Yu, Mohamed S. Zaghloul, Hongcheng Zhu, Andrew M. Scott

Bibliographic record

VenueThe Lancet Oncology · 2024
Typereview
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsBrantford Energy (Canada)Princess Margaret Cancer CentreUniversity of Toronto
FundersNational Cancer InstituteSidney Kimmel Comprehensive Cancer CenterNational Institutes of HealthAustralian and New Zealand Society of Nuclear MedicineUniversität WienEuropean Association of Nuclear MedicineAmgenJohns Hopkins UniversityEuropean SocieTy for Radiotherapy and OncologyDeutsches KrebsforschungszentrumUniversity of WashingtonSociety of Nuclear Medicine and Molecular ImagingAmerican Society for Radiation Oncology
KeywordsRadiation oncologyCommissionRadiation therapyMedical physicsMedicineOncologyInternal medicineBusinessFinance

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.950
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.073
GPT teacher head0.437
Teacher spread0.364 · 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 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

Citations120
Published2024
Admission routes1
Has abstractno

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