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Record W3084137123 · doi:10.1080/16078454.2020.1815130

IgG4 plasma cell myeloma without clinical evidence of IgG4-related disease: a report of two cases

2020· article· en· W3084137123 on OpenAlexaff
Deonne Thaddeus V. Gauiran, Krista Marcon, Mari L. DeMarco, Angela W.S. Fung, Grace van der Gugten, André Mattman, Mollie N. Carruthers, Kevin Song, Luke Y. C. Chen

Bibliographic record

VenueHematology · 2020
Typearticle
Languageen
FieldMedicine
TopicIgG4-Related and Inflammatory Diseases
Canadian institutionsSt. Paul's HospitalVancouver General HospitalUniversity of British Columbia
Fundersnot available
KeywordsIgG4-related diseaseMedicineAutoimmune pancreatitisMultiple myelomaPathologyMonoclonalBeta-2 microglobulinSerum protein electrophoresisAnemiaPlasma cellPolyclonal antibodiesBone marrowInternal medicineGastroenterologyImmunologyAntibodyFibrosisDiseaseMonoclonal antibody

Abstract

fetched live from OpenAlex

: These cases illustrate the importance of performing serum protein electrophoresis in tandem with IgG subclasses to distinguish between polyclonal and monoclonal increases in serum IgG4. The lack of typical IgG4-RD features in these two patients suggests that monoclonal elevation in serum IgG4 alone is insufficient to cause the organ damage characteristic of IgG4-RD. Larger studies of IgG myeloma subtypes are warranted to explore whether IgG1, IgG2, IgG3 and IgG4 myeloma differ in natural history and whether the interference with beta-2 microglobulin is specific to IgG4 monoclonal proteins.

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)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.481
Threshold uncertainty score0.881

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.061
GPT teacher head0.367
Teacher spread0.306 · 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

Citations15
Published2020
Admission routes1
Has abstractyes

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