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Record W4283271244 · doi:10.1038/s41375-022-01613-1

The 5th edition of the World Health Organization Classification of Haematolymphoid Tumours: Myeloid and Histiocytic/Dendritic Neoplasms

2022· review· en· W4283271244 on OpenAlexafffund
Joseph D. Khoury, Éric Solary, Oussama Abla, Yassmine Akkari, Rita Alaggio, Jane F. Apperley, Rafael Bejar, Emilio Berti, Lambert Busque, John K. C. Chan, Weina Chen, Xueyan Chen, Wee Joo Chng, John Choi, Isabel Colmenero, Sarah E. Coupland, Nicholas C.P. Cross, Daphne de Jong, M. Tarek Elghetany, Emiko Takahashi, Jean‐François Emile, Judith A. Ferry, Linda Fogelstrand, Michaëla Fontenay, Ulrich Germing, Sumeet Gujral, Torsten Haferlach, Claire Harrison, Jennelle C. Hodge, Shimin Hu, Joop H. Jansen, Rashmi Kanagal‐Shamanna, Hagop M. Kantarjian, Christian P. Kratz, Xiaoqiu Li, Megan S. Lim, Keith R. Loeb, Sanam Loghavi, Andrea N. Marcogliese, Soheil Meshinchi, Phillip Michaels, Kikkeri N. Naresh, Yasodha Natkunam, Reza Nejati, German Ott, Eric Padron, Keyur P. Patel, Nikhil Patkar, Jennifer Picarsic, Uwe Platzbecker, Irene Roberts, Anna Schuh, William A. Sewell, Reiner Siebert, Prashant Tembhare, Jeffrey Tyner, Srđan Verstovšek, Wei Wang, Brent L. Wood, Wenbin Xiao, Cecilia C.S. Yeung, Andreas Hochhaus

Bibliographic record

VenueLeukemia · 2022
Typereview
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsUniversité de MontréalHôpital Maisonneuve-RosemontHospital for Sick Children
FundersSahlgrenska AkademinNational Cancer InstituteDepartment of Laboratory Medicine and Pathology, University of WashingtonSchool of Medicine, Indiana UniversityUniversity of Texas MD Anderson Cancer CenterUniversitätsklinikum JenaHospital for Sick ChildrenUniversity of California, San DiegoNational University Cancer Institute, SingaporeMedizinischen Hochschule HannoverUniversité de MontréalCentre National de la Recherche ScientifiqueSchool of Medicine, Stanford UniversityFudan UniversityInstitut Gustave-RoussySahlgrenska UniversitetssjukhusetVrije Universiteit AmsterdamUniversity of OxfordWellcome TrustUniversity of SouthamptonUniversity of AlabamaTexas Children's HospitalAmsterdam University Medical CentersMoffitt Cancer CenterInstitut National de la Santé et de la Recherche MédicaleUniversity of WashingtonMemorial Sloan-Kettering Cancer CenterKnight Cancer Institute, Oregon Health and Science UniversityUniversität UlmUniversity of Texas Southwestern Medical CenterImperial College LondonChildren's Hospital Los AngelesNational Institute for Health and Care ResearchAssistance publique-Hôpitaux de ParisMassachusetts General HospitalUniversité Paris-SaclayUniversity of Alabama at BirminghamNationwide Children's HospitalCincinnati Children's Hospital Medical CenterCentre International de Recherche sur le CancerGöteborgs UniversitetRadboud UniversiteitRadboud Universitair Medisch CentrumUniversità degli Studi di MilanoUniversity of Pennsylvania
KeywordsHistiocyteMyeloidDiseaseHematologic NeoplasmsMedicineComputational biologyComputer scienceBiologyPathologyImmunologyCancerInternal medicine

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0090.006
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.008

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 head0.045
GPT teacher head0.338
Teacher spread0.293 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations3,904
Published2022
Admission routes2
Has abstractyes

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