MétaCan
Menu
Back to cohort
Record W2097182839 · doi:10.1186/cc2389

Communication in the Toronto critical care community: important lessons learned during SARS.

2003· article· en· W2097182839 on OpenAlexaffabout
Christopher M. Booth, Thomas E. Stewart

Bibliographic record

VenueCritical Care · 2003
Typearticle
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsUniversity of TorontoUniversity Health NetworkMount Sinai Hospital
Fundersnot available
KeywordsStaffingMedicineCritically illEconomic shortageCoronavirus disease 2019 (COVID-19)Health careOutbreakNursingMedical emergencyIntensive care medicineVirologyInfectious disease (medical specialty)Disease

Abstract

fetched live from OpenAlex

The SARS outbreak in 2003 pushed Toronto's health care system to its limits. Staffing shortages, transmission of SARS within the ICU, and the influx of critically ill SARS patients were some unique challenges to the delivery of critical care. Communication strategies were a key component in the critical care response to SARS. Regular teleconference calls, web-based training and education, and the rapid coordination of research studies were some of the initiatives developed within the Toronto critical care community during the SARS outbreak. Other critical care communities should consider their communication strategies in advance of similar events.

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)0.001
metaresearch head score (Gemma)0.027
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.592
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.027
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
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 head0.239
GPT teacher head0.495
Teacher spread0.256 · 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.

Study designQualitative
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

Citations40
Published2003
Admission routes2
Has abstractyes

Explore more

Same venueCritical CareSame topicFamily and Patient Care in Intensive Care UnitsFrench-language works237,207