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Record W4411021324 · doi:10.1016/j.annonc.2025.05.540

What is required to deliver practice-changing neoadjuvant trials in kidney cancer? An International Neoadjuvant Kidney Cancer Consortium Delphi study

2025· letter· en· W4411021324 on OpenAlexaff
Sabrina H. Rossi, Toni K. Choueiri, Michael Jewett, James O. Jones, Alexander Laird, Ben Lewis, Zayd Tippu, J C Koen van der Mijn, Axel Bex, Grant D. Stewart

Bibliographic record

VenueAnnals of Oncology · 2025
Typeletter
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineKidney cancerCancerNeoadjuvant therapyDelphiDelphi methodOncologyInternal medicineBreast cancer

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.391
metaresearch head score (Gemma)0.572
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.391
Threshold uncertainty score0.751

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3910.572
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0080.006
Scholarly communication0.0070.008
Open science0.0030.008
Research integrity0.0130.015
Insufficient payload (model declined to judge)0.0060.001

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 head0.372
GPT teacher head0.593
Teacher spread0.221 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
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

Citations4
Published2025
Admission routes1
Has abstractno

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