MétaCan
Menu
Back to cohort
Record W4312424111 · doi:10.23977/jemm.2022.070404

Research on the Design of Children's Stroller Based on User Experience

2022· article· en· W4312424111 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.

venuePublished in a venue whose home country is Canada.
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 Engineering Mechanics and Machinery · 2022
Typearticle
Languageen
FieldComputer Science
TopicPersona Design and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsHuman factors and ergonomicsPoison controlInjury preventionSuicide preventionOccupational safety and healthSet (abstract data type)EngineeringHuman–computer interactionTransport engineeringComputer scienceMedical emergencyMedicine

Abstract

fetched live from OpenAlex

With the improvement of people's living standard, people put forward higher requirements for children's stroller. The children's stroller only with strong functionality and high safety can no longer meet the standard of good experience for users. This paper takes the user demand as the guide, finds the pain points and design opportunities of the children's stroller by establishing the user behavior map. Combined with the hierarchy of user experience needs, this paper makes a design and research on children's stroller, and finally puts forward a set of design scheme, which is expected to provide reference for the improvement of the user experience of children's stroller.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.953
Threshold uncertainty score0.183

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 science0.0010.000
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 head0.041
GPT teacher head0.277
Teacher spread0.235 · 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