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Record W4411479312 · doi:10.1097/jce.0000000000000713

Remote Biomedical Services Support Program

2025· article· en· W4411479312 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Clinical Engineering · 2025
Typearticle
Languageen
FieldHealth Professions
TopicQuality and Safety in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsWorkflowService (business)VendorProcess (computing)PhoneDowntimeEngineering managementComputer scienceTelemedicineEngineeringBusinessHealth care

Abstract

fetched live from OpenAlex

During the COVID-19 pandemic, the Biomedical Engineering team at the University of Ottawa Heart Institute (UOHI) faced challenges coordinating with external medical equipment vendors’ service experts due to travel restrictions. Although the UOHI BME team is highly skilled and capable of addressing many equipment issues in-house, certain specialized or vendor-specific interventions still require external input. With most vendors and their support teams located outside Ottawa, UOHI Biomed explored alternative solutions during the pandemic to ensure timely remote service support, minimize delays, reduce equipment downtime, and control costs. This paper outlines an attempt by the Biomedical Engineering department at UOHI to explore a Remote Service Support Program (RSSP) aimed at improving the process of obtaining assistance from vendors by enabling remote connections between Biomedical Engineering Technologists (BMETs) and medical equipment service experts through live, real-time calls. Although the program offered features such as hands-free maintenance support and the ability for remote experts to share documents or screenshots, it ultimately did not integrate well with the department’s established workflows. Furthermore, although several manufacturers had existing remote support platforms, in practice, BMETs continued to rely on familiar tools such as video calls, phone calls, or general-purpose communication platforms when needed. As a result, the Remote Service Support program was not adopted for sustained use.

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)0.006
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.890
Threshold uncertainty score0.945

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.133
GPT teacher head0.599
Teacher spread0.466 · 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