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Record W4394074073 · doi:10.6084/m9.figshare.22623841

Additional file 2 of Health equity related challenges and experiences during the rapid implementation of virtual care during COVID-19: a multiple case study

2023· dataset· en· W4394074073 on OpenAlexaff
Simone Shahid, Sophie Hogeveen, Philina Sky, Shivani Chandra, Suman Budhwani, Ryan de Silva, R. Sacha Bhatia, Emily Seto, James Shaw

Bibliographic record

VenueFigshare · 2023
Typedataset
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsInstitute for Clinical Evaluative SciencesUniversity Health NetworkUniversity of TorontoMcMaster UniversityWomen's College Hospital
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Equity (law)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Health equityHealth careBusinessPsychologyMedicinePolitical scienceVirologyEconomicsEconomic growthInfectious disease (medical specialty)Law

Abstract

fetched live from OpenAlex

Additional file 2: Table S2. Strategies Implemented during the Rapid Implementation of Virtual Care. Table S2 details the strategies used by organizations offering virtualized services to structurally marginalized communities and offers illustrative quotations.

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)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.613
Threshold uncertainty score0.552

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.033
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.007
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.6130.087

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 head0.114
GPT teacher head0.423
Teacher spread0.309 · 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.

Study designQualitative
Domainnot available
GenreDataset

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
Published2023
Admission routes1
Has abstractyes

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