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Record W2907163204 · doi:10.4084/mjhid.2019.007

Bortezomib maintenance for the treatment of Monoclonal Gammopathy of Renal Significance

2019· article· en· W2907163204 on OpenAlexaff
Holly Lee, Peter Duggan, Ernesta Paola Neri, Jason Tay, Victor J Jimenez Zepeda

Bibliographic record

VenueMediterranean Journal of Hematology and Infectious Diseases · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAmyloidosis: Diagnosis, Treatment, Outcomes
Canadian institutionsBaker Hughes (Canada)University of Calgary
Fundersnot available
KeywordsMedicineBortezomibMultiple myelomaMonoclonalWaldenstrom macroglobulinemiaMonoclonal gammopathy of undetermined significanceclone (Java method)Internal medicineKidneyChronic lymphocytic leukemiaMonoclonal antibodyOncologyImmunologyPathologyLeukemiaAntibodyLymphomaBiology

Abstract

fetched live from OpenAlex

Monoclonal gammopathy of renal significance (MGRS) defines renal diseases resulting from the nephrotoxic effects of monoclonal proteins secreted from non-malignant clonal B cells or plasma cells, that do not meet criteria for multiple myeloma, Waldenstrom's macroglobulinemia, chronic lymphocytic leukemia, or lymphomas. Renal disease in MGRS can result from monoclonal immunoglobulin deposition to different parts of the kidney and includes a wide spectrum of glomerular, tubulointerstitial and vascular renal diseases. Recognizing MGRS is important because renal outcomes are poor and treatments targeting the underlying clonal disease have been associated with improved renal survival. In this case report, we present a case of a patient with proliferative glomerulonephritis with monoclonal immunoglobulin deposits (PGNMID) subtype of MGRS who underwent a phased clone directed treatment of induction and extended maintenance therapy to achieve renal response.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.677
Threshold uncertainty score0.402

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.258
Teacher spread0.248 · 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 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

Citations6
Published2019
Admission routes1
Has abstractyes

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