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Record W2154196037 · doi:10.1586/14737140.2014.868776

Getting to the root of the problem: the causes of relapse in multiple myeloma

2014· editorial· en· W2154196037 on OpenAlexaff
Kim Chan Chung, Rodger E. Tiedemann

Bibliographic record

VenueExpert Review of Anticancer Therapy · 2014
Typeeditorial
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineProteasomeMultiple myelomaProgenitor cellContext (archaeology)Cancer researchBortezomibProteasome inhibitorDiseaseOncologyImmunologyStem cellInternal medicineBiologyCell biology

Abstract

fetched live from OpenAlex

Multiple myeloma (MM) remains incurable, and ultimately, patients exhibit disease progression under current treatment regimens. Proteasome inhibitors have emerged as frontline treatment of relapsed and refractory MM however, resistance to these drugs occur through poorly defined mechanisms. Numerous studies have identified different acquired resistance models such as β5 proteasome subunit mutations and stabilization of tumor suppressors and apoptotic proteins. In addition, recent findings have identified a progenitor organization in MM whereby early progenitor tumor cells show resistance to proteasome inhibitor therapy and cause progressive disease with maturation arrest. This editorial highlights the potential causes of MM relapse in the context of these tumor progenitor cells and the role these cells play in treatment failure.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.108
Threshold uncertainty score0.575

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.026
GPT teacher head0.362
Teacher spread0.336 · 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.

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

Citations13
Published2014
Admission routes1
Has abstractyes

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