MétaCan
Menu
Back to cohort
Record W2038498656 · doi:10.1057/jos.2014.23

A simulation model for capacity planning in community care

2014· article· en· W2038498656 on OpenAlex
Jonathan Patrick, Kenneth Nelson, Daniel E. Lane

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.

Bibliographic record

VenueJournal of Simulation · 2014
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Operations and Scheduling Optimization
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsCapacity planningComputer scienceDownstream (manufacturing)ServerHomogeneousOrder (exchange)Capacity managementLong-term careOperations researchBusinessComputer networkMedicineNursingMarketing

Abstract

fetched live from OpenAlex

Sustainable health care requires the building of sufficient capacity in order to ensure that patients receive the right care in a timely fashion. Often the efficient use of available capacity at one level (ie, acute care) is hindered by insufficient capacity at a downstream level (ie, long-term care (LTC)). This paper provides a simulation that helps determine the necessary downstream capacity in LTC in order to maintain smooth patient flow out of the hospitals in the region while still maintaining wait times within a target for those accessing LTC directly from the community. The model is complicated by multiple demand classes, client preferences, competing performance metrics, clients transferring between servers (ie, LTC facilities), significant wait time-dependent reneging and non-homogeneous servers. We provide policy recommendations for capacity planning in the region both for LTC and for supportive housing.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.498
Threshold uncertainty score0.516

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.249
GPT teacher head0.505
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