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Record W2041386089 · doi:10.1177/154193120404801531

A User-Centered Evaluation of three Intravenous Infusion Pumps

2004· article· en· W2041386089 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.

Bibliographic record

VenueProceedings of the Human Factors and Ergonomics Society Annual Meeting · 2004
Typearticle
Languageen
FieldMedicine
TopicHealthcare Technology and Patient Monitoring
Canadian institutionsUniversity of TorontoUniversity of Calgary
Fundersnot available
KeywordsUsabilitySAFERCategorizationHeuristic evaluationComputer scienceCognitive walkthroughFeature (linguistics)PrioritizationUsability inspectionHuman–computer interactionEngineeringArtificial intelligenceProcess managementComputer security

Abstract

fetched live from OpenAlex

Considerable research has focused on whether medical equipment can be made safer/more effective using user-centered design principles. Medication errors may result from improper operation, mechanical failure, and tampering. The present study evaluated the effectiveness and advantages of three intravenous infusion pumps. Five evaluators used heuristic evaluation to identify, categorize, and prioritize usability problems. Positive and negative features were classified according to usability and design principles. The most common negative feature was difficulty setting up an infusion. The most common positive feature was visual feedback regarding pump status. The methodology was effective at identifying a number of problems. Ongoing research involves testing domain-experts to validate the severity of the usability problems identified and discover other safety-relevant errors.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score0.389

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 communication0.0000.000
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 head0.048
GPT teacher head0.294
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