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Record W3085566790 · doi:10.1080/24745332.2020.1769436

Position statement from the Canadian Thoracic Society (CTS) on clinical triage thresholds in respiratory disease patients in the event of a major surge during the COVID-19 pandemic

2020· article· en· W3085566790 on OpenAlexaffabout
Samir Gupta, Jane Batt, Jean Bourbeau, Kenneth R. Chapman, Andrea S. Gershon, John Granton, Nathan Hambly, Paul Hernandez, Martin Kolb, Sanjay Mehta, Lisa Mielniczuk, Steeve Provencher, Anne L. Stephenson, John R. Swiston, D. Elizabeth Tullis, Nicholas T. Vozoris, Joshua Wald, Jason Weatherald, Mohit Bhutani

Bibliographic record

VenueCanadian Journal of Respiratory Critical Care and Sleep Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsUniversity of AlbertaUniversity of CalgaryUniversity of British ColumbiaUniversité LavalLondon Health Sciences CentreToronto General HospitalMcMaster UniversityInstitut universitaire de cardiologie et de pneumologie de QuébecSt. Joseph’s Healthcare HamiltonLibin Cardiovascular Institute of AlbertaUniversity Health NetworkHealth Sciences CentreSinai Health SystemUniversity of OttawaMcGill University Health CentreSt. Michael's HospitalSunnybrook Health Science CentreDalhousie UniversityWestern UniversityUniversity of Toronto
Fundersnot available
KeywordsPandemicCoronavirus disease 2019 (COVID-19)TriageSurge CapacityEvent (particle physics)2019-20 coronavirus outbreakMedicineSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Position statementMedical emergencyIntensive care unitHealth careIntensive care medicineDiseaseEmergency medicineVirologyPolitical sciencePathologyFamily medicineInfectious disease (medical specialty)Outbreak

Abstract

fetched live from OpenAlex

With the rapid rise in cases of COVID-19 across the world, health systems face unprecedented challenges in the delivery of patient care. This includes constrained capacity for intensive care unit (...

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation 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 score0.296
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.123
GPT teacher head0.401
Teacher spread0.278 · 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 teacher head, 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

Citations5
Published2020
Admission routes2
Has abstractyes

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