MétaCan
Menu
Back to cohort
Record W3128398310 · doi:10.1016/j.xkme.2020.12.005

Feasibility of Twice-Weekly Hemodialysis: Contingency Planning for COVID-19

2021· article· en· W3128398310 on OpenAlexaffabout
David A. Clark, Kenneth A. West, Karthik Tennankore

Bibliographic record

VenueKidney Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicineHemodialysisPandemicDialysisIntensive care medicinePopulationHome hemodialysisEmergency medicineInternal medicineCoronavirus disease 2019 (COVID-19)DiseaseInfectious disease (medical specialty)Environmental health

Abstract

fetched live from OpenAlex

Patients receiving facility-based hemodialysis represent a unique and vulnerable population during the coronavirus disease 2019 (COVID-19) pandemic. These individuals require life-sustaining treatment on average 3 times weekly at a dialysis center and cannot remain isolated at home. For each treatment, patients regularly interact with transportation workers, other dialysis patients, and members of the health care team. This places them at heightened risk for acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection.

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)0.003
metaresearch head score (Gemma)0.016
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 score0.025
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.000
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0250.002

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 head0.087
GPT teacher head0.382
Teacher spread0.295 · 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

Citations2
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueKidney MedicineSame topicDialysis and Renal Disease ManagementFrench-language works237,207