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Record W3093120364 · doi:10.3324/haematol.2020.259093

The survival impact of maintenance lenalidomide: an analysis of real-world data from the Canadian Myeloma Research Group national database

2020· article· en· W3093120364 on OpenAlexafffundabout
Hannah Cherniawsky, Vishal Kukreti, Donna Reece, Esther Masih‐Khan, Arleigh McCurdy, Victor H. Jimenez‐Zepeda, Michaël Sébag, Kevin Song, Darrell White, Julie Stakiw, Richard LeBlanc, Tony Reiman, Muhammad Aslam, Martha Louzada, Rami Kotb, Engin Gul, Eshetu G. Atenafu, Christopher P. Venner

Bibliographic record

VenueHaematologica · 2020
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsHôpital Maisonneuve-RosemontDalhousie UniversitySaint John Regional HospitalPrincess Margaret Cancer CentreVancouver General HospitalMcGill UniversityCancerCare ManitobaOttawa HospitalUniversité de MontréalUniversity of SaskatchewanQueen Elizabeth II Health Sciences CentreUniversity of Alberta
FundersDalhousie UniversityUniversity of AlbertaCelgeneSanofiAmgenPfizerMcGill University
KeywordsLenalidomideMultiple myelomaMedicineDatabaseOncologyInternal medicineComputer science

Abstract

fetched live from OpenAlex

The survival impact of maintenance lenalidomide: an analysis of real-world data from the Canadian Myeloma Research Group national database ‡ Fisher's exact test.Ig: immunglobulin; ISS: injury severity score; Cy: cyclophosphamide; V: bortezomid (also abbreviated as Bor in standard combination regime).

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.079
Threshold uncertainty score0.159

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.024
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.014
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0030.001
Research integrity0.0010.001
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 head0.332
GPT teacher head0.467
Teacher spread0.135 · 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 source (direct Gemma or distilled Codex), 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

Citations16
Published2020
Admission routes3
Has abstractno

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