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Record W3003488950 · doi:10.1016/j.clml.2020.01.017

Consensus Guidelines on the Diagnosis of Multiple Myeloma and Related Disorders: Recommendations of the Myeloma Canada Research Network Consensus Guideline Consortium

2020· review· en· W3003488950 on OpenAlexafffundabout
Debra Bergstrom, Rami Kotb, Martha Louzada, Heather J. Sutherland, Sofia Tavoularis, Christopher P. Venner, Julie Anne Côté, Richard LeBlanc, Tony Reiman, Michaël Sébag, Kevin Song, Gabriele Colasurdo, Aldo Del Col, David P. McMullen, Annette E. Hay, Nicole M.B. Laferriere, Arleigh McCurdy, Jean Roy, Julie Stakiw, Suzanne Trudel, Darrell White, Fraser W. Loveys, Edward Randell, Kamilia Rizkalla

Bibliographic record

VenueClinical Lymphoma Myeloma & Leukemia · 2020
Typereview
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsUniversity of AlbertaUniversity of British ColumbiaWestern UniversityUniversity of ManitobaLondon Health Sciences CentreVancouver General HospitalCancerCare ManitobaMemorial University of Newfoundland
FundersMemorial University of NewfoundlandQueen's UniversityCentre Hospitalier Universitaire de QuébecSaskatchewan Cancer Agency
KeywordsGuidelineMultiple myelomaConsensus conferenceMedicineFamily medicineIntensive care medicinePathologyImmunologyInternal medicine

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.005
metaresearch head score (Gemma)0.047
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.753
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.047
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0000.002
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
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 head0.179
GPT teacher head0.438
Teacher spread0.260 · 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 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

Citations47
Published2020
Admission routes3
Has abstractno

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