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Record W4411152766 · doi:10.1038/s41588-025-02251-w

Author Correction: Comprehensive molecular profiling of multiple myeloma identifies refined copy number and expression subtypes

2025· erratum· en· W4411152766 on OpenAlexaff
Sheri Skerget, Daniel Peñaherrera, Ajai Chari, Sundar Jagannath, David S. Siegel, Ravi Vij, Gregory Orloff, Andrzej Jakubowiak, Rubén Niesvizky, Darla Liles, Jesús G. Berdeja, Moshe Levy, Jeffrey L. Wolf, Saad Z. Usmani, Jeffrey A. Zonder, João L. Ascensão, Cristina Gasparetto, Miguel‐Teodoro Hernández, Juan Vazquez Paganini, Pablo Rios, Rebecca Silbermann, Michael P. Chu, Allyson Harroff, Rafaël Fonseca, Gemma Azaceta, Carmen Martínez‐Chamorro, Rama Balaraman, Wayne Harris, Marie Shieh, Adedayo A. Onitilo, Fabio Volterra, William Wachsman, Madhuri Yalamachili, Eugènia Abella, Larry J. Anderson, Joan Bargay, Hani Hassoun, Gerald C Hsu, Hakan Kaya, Alex R. Menter, Dilip Patel, Donald Richards, William B. Solomon, Robert F. Anderson, Sumeet Chandra, Miguel Á. Conde, Saulias Girnius, May Matkiwsky, Isabel Krsnik, Shaji Kumar, Albert Oriol, Paula Rodríguez, Vivek Roy, Shanti Srinivas, Ronald G. Steis, Austin Christofferson, Sara Nasser, Jessica L. Aldrich, Christophe Legendre, Brooks A. Benard, C. S. Miller, Bryce Turner, Ahmet Kurdoglu, Megan Washington, Venkata D. Yellapantula, Jonathan Adkins, Lori Cuyugan, Martin Boateng, Adrienne Helland, Shari Kyman, Jackie McDonald, Rebecca Reiman, Kristi Stephenson, Erica E. Tassone, Alex Blanski, Brianne Livermore, Meghan Kirchhoff, Daniel C. Rohrer, Mattia D’Agostino, Manuela Gambella, Kimberly Collison, Jennifer Stumph, Pam Kidd, Andrea Donnelly, Barbara Zaugg, Maureen Toone, Kyle McBride, Mary DeRome, Jennifer Rogers, David W. Craig, Winnie S. Liang, Norma C. Gutiérrez, Scott D. Jewell, John D. Carpten, Kenneth C. Anderson, Hearn Jay Cho, Daniel Auclair, Sagar Lonial, Jonathan J. Keats

Bibliographic record

VenueNature Genetics · 2025
Typeerratum
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsMcGill UniversityAlberta Cancer FoundationRoyal Victoria HospitalPrincess Margaret Cancer Centre
Fundersnot available
KeywordsBiologyGene expression profilingMultiple myelomaProfiling (computer programming)Computational biologyExpression (computer science)GeneticsGene expressionGeneImmunologyComputer science

Abstract

fetched live from OpenAlex

In the version of the article initially published, Manuela Gambella’s surname appeared incorrectly (as Gamella) and has now been corrected in the HTML and PDF versions of the article.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.004
metaresearch head score (Gemma)0.047
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reproducibility · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.996
Threshold uncertainty score0.155

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.047
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0030.002
Scholarly communication0.0030.002
Open science0.0030.002
Research integrity0.0050.010
Insufficient payload (model declined to judge)0.0460.024

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 head0.017
GPT teacher head0.331
Teacher spread0.314 · 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 designNot applicable
DomainReproducibility
GenreOther

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 abstractyes

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