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Record W4306867613 · doi:10.3324/haematol.2021.280051

Prognostic value of positron emission tomography/computed tomography in transplant-eligible newly diagnosed multiple myeloma patients from CASSIOPEIA: the CASSIOPET study

2022· letter· en· W4306867613 on OpenAlexaff
Françoise Kraeber‐Bodéré, Sonja Zweegman, Aurore Perrot, Cyrille Hulin, Denis Caillot, Thierry Façon, Xavier Leleu, Karim Belhadj, Emmanuel Itti, Lionel Karlin, Clément Bailly, Mark‐David Levin, Monique C. Minnema, Bastien Jamet, Caroline Bodet‐Milin, Marie C. Béné, Hervé Avet‐Loiseau, Pieter Sonneveld, Lixia Pei, Fabio Rigat, Carla de Boer, Jessica Vermeulen, Tobias Kampfenkel, Jérôme Lambert, Philippe Moreau

Bibliographic record

VenueHaematologica · 2022
Typeletter
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsHotel Dieu Hospital
FundersInstitut National Du CancerDirection Générale de l’offre de SoinsInstitut National de la Santé et de la Recherche MédicaleAgence Nationale de la RechercheCHIST-ERALabex Iron
KeywordsPositron emission tomographyMedicineMultiple myelomaCassiopeia APositron Emission Tomography-Computed TomographyNuclear medicineRadiologyTomographyInternal medicinePhysicsAstronomy

Abstract

fetched live from OpenAlex

Funding Information: This study was funded by the Intergroupe Francophone du Myélome (IFM) and the Dutch-Belgian Cooperative Trial Group for Hematology Oncology (HOVON) and was supported in part by grants from the French National Agency for Research called “Investissements d’Avenir” IRON Labex n◦ ANR-11-LABX-0018-01 and by a grant from INCa-DGOS-Inserm_12558 (SIRIC ILIAD).

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.273
Teacher spread0.250 · 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 designObservational
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

Citations27
Published2022
Admission routes1
Has abstractyes

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