MétaCan
Menu
Back to cohort
Record W4306918560 · doi:10.3390/geriatrics7050118

Results of a Continuous Quality Improvement Initiative of the Contemporaneous Model of Service Delivery

2022· article· en· W4306918560 on OpenAlexaffabout
Atul Sunny Luthra, Adam Millar

Bibliographic record

VenueGeriatrics · 2022
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsMcMaster UniversityResearch Institute for Aging
Fundersnot available
KeywordsMedicineNeurocognitiveService delivery frameworkDementiaService (business)Delivery systemHealthcare deliveryBehavioral modelingService modelMedical emergencyHealth care deliveryHealth carePsychiatryCognition

Abstract

fetched live from OpenAlex

The Contemporaneous Model of service delivery serves to manage behavioral expression in residents of long-term care homes with a diagnosis of advanced neurocognitive disorder. Its effectiveness is benchmarked in preventing the residents, on its active caseload, from seeking assistance in the emergency department and the dementia behavioral inpatient units for behavioral risks. The results of the three years of operation of the Contemporaneous Model of service delivery, for the years 2017–2018, 2018–2019, and 2019–2020, are presented here. These results are supportive of this model of service delivery as an effective way to reduce the burden of patients with advanced neurocognitive disorder with behavioral expressions on the emergency departments and specialized dementia behavioral services. It has the potential for becoming the gold standard model of service delivery in the Canadian health care system.

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)0.040
metaresearch head score (Gemma)0.049
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.464
Threshold uncertainty score0.923

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0400.049
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.047
GPT teacher head0.308
Teacher spread0.262 · 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.

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

Citations0
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueGeriatricsSame topicDementia and Cognitive Impairment ResearchFrench-language works237,207