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Record W4391581941 · doi:10.1504/ijlsm.2024.136490

Maintenance excellence and CMMS criteria choice in the context of small hospital and healthcare organisations

2024· article· en· W4391581941 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

VenueInternational Journal of Logistics Systems and Management · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicQuality and Management Systems
Canadian institutionsUniversité du Québec à Rimouski
Fundersnot available
KeywordsExcellenceBusinessContext (archaeology)Health careOperations managementProcess managementMarketingEngineeringEconomicsPolitical scienceGeographyEconomic growth

Abstract

fetched live from OpenAlex

As medical equipment has become more complex and expensive, the maintenance of this equipment requires special attention to improve outcomes and reduce costs notably in the small hospital and healthcare organisations (SHHOC). This research explores how SHHOC can improve maintenance management according to the maintenance employees' views, and what characteristics of CMMS can help these organisations to reach maintenance excellence. Based on qualitative research method, specifically a multi-case study, the research is conducted on 43 of 68 maintenance employees of small material maintenance services in three regions in the Est of Quebec. This research is a very beneficial source of information both for maintenance managers and stakeholders in making decisions about the maintenance excellence program and selection of CMMS. To the best of the authors' knowledge, this paper is the first to address maintenance excellence and CMMS software selection criteria from the maintenance employees' perspective in the SHHOC context.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.947
Threshold uncertainty score0.509

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.039
GPT teacher head0.290
Teacher spread0.251 · 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