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Record W4225666888 · doi:10.1007/s00277-022-04802-1

The impact of oral hypoglycemics and statins on outcomes in myelodysplastic syndromes

2022· article· en· W4225666888 on OpenAlexafffund
Eugène Brailovski, Qing Li, Ning Liu, Brian Leber, Dina Khalaf, Mitchell Sabloff, Grace Christou, Karen Yee, Lisa Chodirker, Anne Parmentier, Mohammed Siddiqui, Alexandre Mamedov, Liying Zhang, Ying Liu, Craig C. Earle, Matthew C. Cheung, Nicole Mittmann, Rena Buckstein, Lee Mozessohn

Bibliographic record

VenueAnnals of Hematology · 2022
Typearticle
Languageen
FieldMedicine
TopicPeptidase Inhibition and Analysis
Canadian institutionsHealth Sciences CentreInstitute for Work & HealthPrincess Margaret Cancer CentreOttawa HospitalUniversity of TorontoSunnybrook Health Science CentreJuravinski Cancer CentreInstitute for Clinical Evaluative Sciences
FundersOntario Institute for Cancer Research
KeywordsMedicineInternal medicineMetforminProportional hazards modelProspective cohort studyObservational studyLower riskUnivariate analysisCohort studyGastroenterologyMultivariate analysisConfidence intervalInsulin

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.026
Threshold uncertainty score0.186

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.057
GPT teacher head0.381
Teacher spread0.324 · 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.

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

Citations3
Published2022
Admission routes2
Has abstractno

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