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Record W4378188863 · doi:10.1038/s41408-023-00856-0

Correction: Integrated analysis of next generation sequencing minimal residual disease (MRD) and PET scan in transplant eligible myeloma patients

2023· erratum· en· W4378188863 on OpenAlexaff
Rodrigo Fonseca, Mariano Arribas, Julia E. Wiedmeier, Yael Kusne, Miguel González Vélez, Heidi Kosiorek, Richard Butterfield, Ilan R. Kirsch, Joseph Mıkhael, A. Keith Stewart, Craig B. Reeder, Jeremy T. Larsen, P. Leif Bergsagel, Rafaël Fonseca

Bibliographic record

VenueBlood Cancer Journal · 2023
Typeerratum
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
FundersNational Cancer Institute
KeywordsMinimal residual diseaseMedicineMultiple myelomaOncologyInternal medicineResidualMedical physicsBone marrowComputer scienceAlgorithm

Abstract

fetched live from OpenAlex

Following the publication of this article the authors noted and error in Figure 4, “Kaplan Meier curves for time to next treatment (TTNT) according to sequential MRD measurements”. The figure should have displayed only patients who had MRD taken at least 1 year apart (as defined by IMWG), but instead it incorrectly included an additional 8 patients with sequential measurements taken only at least 6 months apart.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.244
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.052
GPT teacher head0.315
Teacher spread0.263 · 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 teacher head, not a consensus.

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

Citations1
Published2023
Admission routes1
Has abstractyes

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