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Record W4412870758 · doi:10.24908/pceea.2025.19717

An Innovation Challenge to Stimulate Student Interest in Geriatric Health Technologies

2025· article· en· W4412870758 on OpenAlexafffundvenueabout
Silas Ifeanyi, Christopher Rennick, Nancy Nelson

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2025
Typearticle
Languageen
FieldEngineering
TopicBiomedical and Engineering Education
Canadian institutionsUniversity of Waterloo
FundersUniversity of Toronto
KeywordsBusinessPsychology

Abstract

fetched live from OpenAlex

Canada’s aging population has created significant challenges in geriatric health care, increasing the demand for innovative technological solutions. This paper describes the design and implementation of a weekend-long, interdisciplinary hackathon designed to stimulate student interest in creating technology-based solutions for geriatric health care. Students were presented with the problem of detecting and preventing hospital-induced delirium and provided opportunities to speak with stakeholders from a local hospital throughout the event. In total, 62 students attended the event, 51 from engineering or tech-related programs and 11 from health. Five of the 13 teams of 4-5 students included at least one health student. Of the five problem spaces identified by the activity designers, the majority of groups focussed on patient risk factor monitoring. Overall, the event was judged as a success. Students built functional solutions guided by pre-prepared resources and interactions with key stakeholders including geriatric doctors and volunteers from the hospital elder life program. Planning is underway for the next iteration of the challenge.

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 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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.742
Threshold uncertainty score0.901

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.011
GPT teacher head0.257
Teacher spread0.246 · 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 teacher head, 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
Published2025
Admission routes4
Has abstractyes

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