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Record W4415056368 · doi:10.12927/hcq.2025.27686

Timely, Connected and Person-Centred: How the Integrated interRAI Reporting System Is Supporting Senior Care in Canada

2025· article· en· W4415056368 on OpenAlexaffvenueabout

Bibliographic record

VenueHealthcare Quarterly · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHealthcare Systems and Technology
Canadian institutionsCanadian Institute for Health Information
Fundersnot available
KeywordsStandardizationBenchmark (surveying)Health informaticsBest practiceHealth careLong-term careElderly care

Abstract

fetched live from OpenAlex

The Integrated interRAI Reporting System (IRRS) supports timely, connected and person-centred senior care in Canada. IRRS enables system-to-system communication and near real-time data submission for the home care and long-term care sectors. It houses new interRAI data standards that offer improved commonality and standardization of language. With IRRS, users can explore organizational-level data, compare results across jurisdictions and see trends over time in a dynamic and user-friendly interactive business intelligence tool. IRRS will better support the sectors' ability to respond to emerging pan-Canadian needs to analyze, benchmark and compare data.

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)0.014
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.867
Threshold uncertainty score0.964

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.042
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.008
Science and technology studies0.0120.003
Scholarly communication0.0150.004
Open science0.0040.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.021
GPT teacher head0.251
Teacher spread0.230 · 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 designNot applicable
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
Published2025
Admission routes3
Has abstractyes

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