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Record W4212905602 · doi:10.1016/s2666-7568(22)00009-5

Geriatric risk factors for serious COVID-19 outcomes among older adults with cancer: a cohort study from the COVID-19 and Cancer Consortium

2022· article· en· W4212905602 on OpenAlexafffund
Arielle Elkrief, Cassandra Hennessy, Nicole M. Kuderer, Samuel M. Rubinstein, Elizabeth Wulff‐Burchfield, Rachel Rosovsky, Karen Vega-Luna, Orestis A. Panagiotou, Aakash Desai, Donna R. Rivera, Ali Raza Khaki, Lisa Tachiki, Ryan C. Lynch, Catherine Stratton, Rawad Elias, Gerald Batist, Anup Kasi, Dimpy P. Shah, Ziad Bakouny, Angelo Cabal, Jessica Clément, Jennifer Crowell, Becky Dixon, Christopher R. Friese, Stacy Fry, Punita Grover, Shuchi Gulati, Shilpa Gupta, Clara Hwang, Hina Khan, Soo Jung Kim, Elizabeth J. Klein, Chris Labaki, Rana R. McKay, Amanda Nizam, Nathan A. Pennell, Matthew Puc, Andrew Schmidt, Armin Shahrokni, Justin Shaya, Christopher Su, Sarah Wall, Nicole Williams, Trisha M. Wise‐Draper, Sanjay Mishra, Petros Grivas, Benjamin French, Jeremy L. Warner, Tanya M. Wildes

Bibliographic record

VenueThe Lancet Healthy Longevity · 2022
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsMcGill UniversityJewish General HospitalMcGill University Health Centre
FundersNational Center for Advancing Translational SciencesBeatrice and Samuel A. Seaver FoundationCanadian Institutes of Health ResearchVanderbilt Institute for Clinical and Translational ResearchNational Institute on AgingNational Cancer InstituteNational Institutes of Health
KeywordsMedicineComorbidityOdds ratioCohortCancerGeriatric oncologyInternal medicineLogistic regressionCohort studyCoronavirus disease 2019 (COVID-19)Disease

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.029
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.066
GPT teacher head0.398
Teacher spread0.333 · 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

Citations22
Published2022
Admission routes2
Has abstractyes

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