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Simulation Model of a Multi-Hospital Critical Care Network

2022· article· en· W4317792658 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venue2022 Winter Simulation Conference (WSC) · 2022
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Operations and Scheduling Optimization
Canadian institutionsUniversity of British ColumbiaVancouver General HospitalSimon Fraser University
Fundersnot available
KeywordsIntensive careMedicineCritical care nursingDiscrete event simulationMedical emergencyComputer scienceEmergency medicineIntensive care medicineSimulationHealth care

Abstract

fetched live from OpenAlex

We develop a discrete event simulation model for a network of eight major intensive care units (ICUs) in British Columbia, Canada. The model also contains high acuity units (HAUs) that provide critical care to patients that cannot be cared for in a general medical ward, but do not require the full spectrum of care available in an ICU. We model patient flow within the ICU and HAU for each of the hospitals, as well as patient transfers to address ICU capacity. Included in the model is early discharge from ICU to HAU, sometimes called “bumping”, when the ICU is full, as well as ICU overflow beds. The simulation model, which is calibrated using the British Columbia Critical Care Database, will be used to support planning for critical care capacity under endemic and seasonal COVID-19.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.886
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.161
GPT teacher head0.462
Teacher spread0.301 · 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