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Record W4413092579 · doi:10.1016/j.annonc.2025.05.013

1O Nivolumab (NIVO) plus ipilimumab (IPI) vs NIVO monotherapy for microsatellite instability-high/mismatch repair-deficient (MSI-H/dMMR) metastatic colorectal cancer (mCRC): Health-related quality of life (HRQoL) analyses from CheckMate 8HW

2025· article· en· W4413092579 on OpenAlexaff
E. Elez Fernandez, T. André, S. Lonardi, H.J. Lenz, E. Van Cutsem, R. Garcia-Carbonero, D. Tougeron, G.A. Mendez, M. Schenker, Arnaud de la Fouchardière, Takashi Yoshino, J. Li, Fabienne Aubin, Elena Cela, Huaxin Sheng, Steven I. Blum, K. Davé, L. Jin, L.H. Jensen

Bibliographic record

VenueAnnals of Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsCentre Hospitalier de l’Université de Montréal
FundersCilagSanofi K.K.MSD K.K.Chugai PharmaceuticalGenentechAptitude HealthNordic Pharma GroupMenarini GroupPfizer JapanSociedad Española de Oncología MédicaPharmaMarNovartis FarmacéuticaEuropean Society for Medical OncologyAstellas PharmaEisaiDaiichi-SankyoSeagenG1 TherapeuticsSysmex CorporationBeiGeneLes Laboratories Pierre FabreRegeneron PharmaceuticalsMylanAstraZenecaNovocureIpsenArray BioPharmaJazz PharmaceuticalsPfizerIncyteMerck KGaATaiho PharmaceuticalTakeda Pharmaceutical CompanyAmgenAmerican Association for Cancer ResearchSamsungBristol-Myers SquibbOno PharmaceuticalEli Lilly and CompanyAmerican Society of Clinical OncologyDaiichi Sankyo EuropeServierGilead SciencesExelixisSanofiBayer YakuhinCelgene
KeywordsMedicineNivolumabIpilimumabMicrosatellite instabilityColorectal cancerInternal medicineOncologyCancerImmunotherapyMicrosatelliteGeneGenetics

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)0.001
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: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.170
GPT teacher head0.465
Teacher spread0.295 · 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 designNon-randomized 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

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Same venueAnnals of Oncology→Same topicGenetic factors in colorectal cancer→French-language works237,207→