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Multiple Myeloma Surveillance Counterpoint: Canada

2012· book-chapter· en· W322081330 on OpenAlexaffabout
Matthew C. Cheung, Kevin Imrie

Bibliographic record

VenueHumana Press eBooks · 2012
Typebook-chapter
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMultiple myelomaCounterpointMedicineBone marrowCancerMonoclonalPlasma cell neoplasmPlasma cellInternal medicineOncologyPathologyMonoclonal antibodyImmunologyAntibodyPsychology

Abstract

fetched live from OpenAlex

Multiple myeloma is a mature B-cell neoplasm originating in the bone marrow characterized by a serum monoclonal protein, plasma cell proliferation in the bone marrow, and skeletal destruction [1]. In 2008, the Canadian Cancer Society projected that 2,100 Canadians would be diagnosed with this cancer and that 1,350 would die from the disease [2]. Prior to the mid-1990s, myeloma was managed palliatively with steroids and oral alkylating agents. With such an approach, patients rarely attained prolonged remissions and were generally on active treatment for much of the time from diagnosis to death, which was typically only 2–4 years [3]. Given this, well follow-up visits were relevant to only a small proportion of patients, generally for short windows of time.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.168
Threshold uncertainty score0.337

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0530.005

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 head0.059
GPT teacher head0.277
Teacher spread0.218 · 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

Citations0
Published2012
Admission routes2
Has abstractyes

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