MétaCan
Menu
Back to cohort
Record W4285286727 · doi:10.1007/978-3-031-09593-1_8

Toward a Trip Planner Adapted to Older Adults Context: Mobilaînés Project

2022· book-chapter· en· W4285286727 on OpenAlexaff
Bessam Abdulrazak, Sahar Tahir, Souhail Maraoui, Véronique Provencher, Dany Baillargeon

Bibliographic record

VenueLecture notes in computer science · 2022
Typebook-chapter
Languageen
FieldEngineering
TopicTransportation and Mobility Innovations
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsPlannerComputer scienceSocializationContext (archaeology)Public transportHuman–computer interactionTransport engineeringArtificial intelligencePsychologyEngineeringSocial psychology

Abstract

fetched live from OpenAlex

Abstract Mobility is essential for older adults to keep a good level of socialization, health and well-being. Still, aging is often accompanied by multiple mobility-related challenges. Hence, these mobility limitations make travel and use of public transport a big challenge. Numerous mobility trip planner tools can be found now days. However, they are not adapted to older adults’ needs and preferences. We discuss in this paper our attempt to develop a one-stop platform to help older adults in their mobility where, when, and how they want. We introduce our co-creation approach, our software architecture, as well as our first prototype.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.975
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.021
GPT teacher head0.241
Teacher spread0.220 · 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.

Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations2
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueLecture notes in computer scienceSame topicTransportation and Mobility InnovationsFrench-language works237,207