MétaCan
Menu
← Back to cohort

Additional file 1 of Critical care capacity in Canada: results of a national cross-sectional study

2021· article· en· W6958437498 on OpenAlexaffabout

Bibliographic record

VenueFigshare · 2021
Typearticle
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsLawson Health Research InstituteMcMaster UniversityKelowna General HospitalAlberta Health ServicesUniversity of AlbertaUniversity of ManitobaCentre hospitalier universitaire de QuébecUniversity of British ColumbiaCentre Hospitalier Universitaire de SherbrookeVancouver General HospitalRoyal Jubilee HospitalSunnybrook HospitalMemorial University of NewfoundlandUniversity Health NetworkUniversity of Alberta HospitalPublic Health Agency of CanadaCentre Hospitalier Universitaire Sainte-JustineDalhousie UniversityRoyal University HospitalUniversity of Toronto
Fundersnot available
KeywordsCensusMechanical ventilationPopulationVentilation (architecture)Intensive care

Abstract

fetched live from OpenAlex

Contains Figure S1A showing ICU beds capable of invasive mechanical ventilation per 100,000 Canadian population according to census division, Figure S2 showing the relationship between number of ICU beds capable of ventilation and population by health region, and Figure S3 showing the relationship between number of ICU beds capable of ventilation and population by census division, and contains the mapping methodology technical notes and the Canadian Critical Care Trials Group Capacity Survey.

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)0.001
metaresearch head score (Gemma)0.015
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.405
Threshold uncertainty score0.848

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.011
Science and technology studies0.0030.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.4050.019

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 head0.212
GPT teacher head0.367
Teacher spread0.156 · 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 designNot applicable
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
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueFigshare→Same topicSepsis Diagnosis and Treatment→French-language works237,207→