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Record W3208273355 · doi:10.1111/bjh.17946

The future of myeloma research in Canada and beyond: results of a James Lind Alliance priority setting partnership

2021· letter· en· W3208273355 on OpenAlexaffabout
Samantha Fowler, Lauren P. McLaughlin, Sarah Bridges, Marc Robichaud, Barbara Ridgway, Donna Reece, Kevin Song, Lorelei Dalrymple, Robin Sully, Sharon Nason, Suzanne Rowland, Trish MacDonald, William Paine, Tony Reiman

Bibliographic record

VenueBritish Journal of Haematology · 2021
Typeletter
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsDalhousie UniversityUniversity of New BrunswickPrincess Margaret Cancer CentreEssar Steel Algoma (Canada)Saint John Regional HospitalVancouver General HospitalUniversité de MonctonHorizon Health Network
Fundersnot available
KeywordsMultiple myelomaMedicineGeneral partnershipAllianceQuality of life (healthcare)DiseaseIntensive care medicineInternal medicinePolitical scienceNursing

Abstract

fetched live from OpenAlex

The British Journal of Haematology publishes original research papers in clinical, laboratory and experimental haematology. The Journal also features annotations, reviews, short reports, images in haematology and Letters to the Editor.

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)0.101
metaresearch head score (Gemma)0.102
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.922
Threshold uncertainty score0.890

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1010.102
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.008
Science and technology studies0.0290.009
Scholarly communication0.0270.009
Open science0.0050.026
Research integrity0.0070.011
Insufficient payload (model declined to judge)0.0100.001

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 head0.040
GPT teacher head0.334
Teacher spread0.294 · 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.

Study designNot applicable
DomainMethods
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
Published2021
Admission routes2
Has abstractyes

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