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Record W4385188419 · doi:10.1136/bmj-2023-075148

The predictable crisis of covid-19 in Canada’s long term care homes

2023· article· en· W4385188419 on OpenAlexafffundabout
Carole A. Estabrooks, Vivian Ewa, Janice Keefe, Sharon E. Straus

Bibliographic record

VenueBMJ · 2023
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsMount Saint Vincent UniversitySt. Michael's HospitalUniversity of CalgaryUniversity of Alberta
FundersHealth CanadaCanada Research ChairsPublic Health AgencyPublic Health Agency of Canada
KeywordsCoronavirus disease 2019 (COVID-19)PandemicLong-term care2019-20 coronavirus outbreakTerm (time)SafeguardSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Economic growthPolitical sciencePublic administrationMedicineNursingLawEconomicsVirologyOutbreak

Abstract

fetched live from OpenAlex

Sharon Straus and colleagues argue that residents, families, and staff in long term care homes in Canada were failed by governments during the pandemic and need coordinated efforts across federal, provincial, and territorial governments to safeguard these populations

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)0.005
metaresearch head score (Gemma)0.011
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 score0.870
Threshold uncertainty score0.945

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0260.012
Scholarly communication0.0100.004
Open science0.0030.007
Research integrity0.0090.019
Insufficient payload (model declined to judge)0.0100.001

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 head0.043
GPT teacher head0.404
Teacher spread0.361 · 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

Citations30
Published2023
Admission routes3
Has abstractyes

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