MétaCan
Menu
← Back to cohort
Record W4282033105 · doi:10.1056/nejmoa2203478

Teclistamab in Relapsed or Refractory Multiple Myeloma

2022· article· en· W4282033105 on OpenAlexaff
Philippe Moreau, Alfred L. Garfall, Niels W.C.J. van de Donk, Hareth Nahi, Jesús F. San Miguel, Albert Oriol, Ajay K. Nooka, Thomas G. Martin, Laura Rosiñol, Ajai Chari, Lionel Karlin, Lotfi Benboubker, María‐Victoria Mateos, Nizar J. Bahlis, Rakesh Popat, Britta Besemer, Joaquín Martínez‐López, Surbhi Sidana, Michel Delforge, Lixia Pei, Danielle Trancucci, Raluca Verona, Suzette Girgis, Shun Xin Wang Lin, Yunsi Olyslager, Mindy Jaffe, Clarissa Uhlar, Tara Stephenson, Rian Van Rampelbergh, Arnob Banerjee, Jenna D. Goldberg, Rachel Kobos, Amrita Krishnan, Saad Z. Usmani

Bibliographic record

VenueNew England Journal of Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsUniversity of CalgaryInstitute of Cancer ResearchHotel Dieu Hospital
FundersJanssen Research and DevelopmentWinship Cancer InstituteSchool of Medicine, Stanford UniversityCancer Center AmsterdamCentro de Investigación Biomédica en Red de CáncerEberhard Karls Universität TübingenNational Cancer InstituteInstitut d’Investigacions Biomèdiques August Pi i Sunyer, Universitat de BarcelonaEmory UniversityUniversidad de NavarraUniversity College LondonMemorial Sloan-Kettering Cancer CenterPerelman School of Medicine, University of PennsylvaniaUniversitat de BarcelonaVrije Universiteit AmsterdamUniversity of PennsylvaniaUniversity of California, San FranciscoComprehensive Cancer Center, City of HopeNational Institute for Health and Care ResearchLeukemia and Lymphoma Society
KeywordsMultiple myelomaRefractory (planetary science)AntibodyCancer researchAntigenMedicineCD3ImmunologyBiologyCD8

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.000
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.041
GPT teacher head0.324
Teacher spread0.283 · 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

Citations1,114
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueNew England Journal of Medicine→Same topicMultiple Myeloma Research and Treatments→French-language works237,207→