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Record W4412881860 · doi:10.21203/rs.3.rs-7159624/v1

Neoadjuvant immune-modulating SBRT and anti-CD73 to increase response to anti-PD-L1 and chemotherapy in early ER+/HER2- breast cancer: primary endpoint and translational results from the randomized Neo-CheckRay trial

2025· preprint· en· W4412881860 on OpenAlexaff
Alex De Caluwé, Isabelle Desmoulins, Kim Cao, Vincent Remouchamps, Adinda Baten, E. Longton, Karine Peignaux, Andrea Joaquin Garcia, Luca Arecco, Elisa Agostinetto, Guilherme Nader Marta, Zoë Denis, Jennifer Dhont, Paulus Kristanto, Xavier Catteau, Denis Larsimont, Roberto Salgado, Philip Poortmans, John Stagg, Christos Sotiriou, Martine Piccart, Michail Ignatiadis, Emanuela Romano, Laurence Buisseret

Bibliographic record

VenueResearch Square · 2025
Typepreprint
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsCentre Hospitalier de l’Université de MontréalHôpital Saint-Luc
FundersAstraZeneca
KeywordsClinical endpointMedicineBreast cancerInternal medicineOncologyPopulationChemotherapyImmune systemCancerGastroenterologyRandomized controlled trialImmunology

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.028
GPT teacher head0.364
Teacher spread0.337 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
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 abstractno

Explore more

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