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Record W4210632919 · doi:10.1016/s2352-3026(21)00283-0

Consensus guidelines and recommendations for infection prevention in multiple myeloma: a report from the International Myeloma Working Group

2022· review· en· W4210632919 on OpenAlex
Noopur Raje, Elias Anaissie, Shaji Kumar, Sagar Lonial, Thomas G Martin, Morie A. Gertz, Amrita Krishnan, Parameswaran Hari, Heinz Ludwig, Elizabeth O’Donnell, Andrew J. Yee, Jonathan L. Kaufman, Adam D. Cohen, Laurent Garderet, Ashutosh F Wechalekar, Evangelos Terpos, Navin Khatry, Rubén Niesvizky, Qing Yi, Douglas Joshua, Tapan Saikia, Nelson Leung, Monika Engelhardt, Mohamad Mothy, Andrew R. Branagan, Ajai Chari, Tony Reiman, Brea Lipe, Joshua Richter, S. Vincent Rajkumar, Jesús F. San Miguel, Kenneth C. Anderson, Edward A. Stadtmauer, Rao Prabhala, Phillip McCarthy, Nikhil C. Munshi

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Lancet Haematology · 2022
Typereview
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsSaint John Regional Hospital
Fundersnot available
KeywordsMedicineMultiple myelomaIntensive care medicineContext (archaeology)VaccinationDiseaseImmunologyInternal 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.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.970
Threshold uncertainty score0.605

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.332
GPT teacher head0.457
Teacher spread0.125 · 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