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Record W4300963362 · doi:10.47326/ocsat.2022.03.67.1.0

Brief on Primary Care Part 1: The Roles of Primary Care Clinicians and Practices in the First Two Years of the COVID-19 Pandemic in Ontario

2022· report· en· W4300963362 on OpenAlexfundaboutno aff
Tara Kiran, Azza Eissa, Dee Mangin, Imaan Bayoumi, Noah Ivers, Sarah Newbery, Elizabeth Muggah, Jennifer Rayner, Dominik Alex Nowak, Liisa Jaakkimainen, Michael Green, Susan Beazley, David M. Kaplan, Victoria Haldane, Andrew D. Pinto, Beth Cowper-Fung, Allan Grill, Nicolas S. Bodmer, Anna Perkhun, Kamila Premji, Steve Nastos, Claudia Mariano, Onil Bhattacharyya, Sally Hall Dykgraaf, Michael Kidd, Rosemarie Lall, Katherine J. Miller, Onyenyechukwu Nnorom, Suzanne Shoush, Janet Smylie, James Wright, Richard H. Glazier, Fahad Razak, Karen Born, Danielle Martin

Bibliographic record

Venuenot available
Typereport
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsnot available
FundersUniversity of TorontoMcMaster University
KeywordsPandemicPrimary careCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Primary (astronomy)MedicineFamily medicineVirologyOutbreakPathologyInfectious disease (medical specialty)Disease

Abstract

fetched live from OpenAlex

Primary care is a critical entry point into both COVID-19- and non-COVID-19-related care in Ontario. Primary care clinicians (PCCs) played an integral and multi-faceted role in Ontario’s pandemic response. This included a rapid transition to virtual care; participating in testing, treatment, and wraparound services for COVID-19; providing education and support to local communities to increase vaccine uptake; and more recently, catching up with non-COVID care despite fixed resources. COVID-19 care is increasingly being integrated into primary care practices but without added resources or supports. At the same time, PCCs are supporting patients who experienced missed or delayed care through the pandemic. Practices funded to include interprofessional teams have inherently had more flexibility to support both the pandemic response and catch-up of non-COVID-19 care.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.947
Threshold uncertainty score0.385

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0100.002
Scholarly communication0.0040.002
Open science0.0020.003
Research integrity0.0090.005
Insufficient payload (model declined to judge)0.0290.005

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 head0.143
GPT teacher head0.426
Teacher spread0.282 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations17
Published2022
Admission routes2
Has abstractyes

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