MétaCan
Menu
Back to cohort
Record W2586486982 · doi:10.1007/978-3-319-49879-9

Recent Advances in Technologies for Inclusive Well-Being: From Worn to Off-body Sensing, Virtual Worlds, and Games for Serious Applications

2017· book· en· W2586486982 on OpenAlexaff
Anthony Lewis Brooks, Sheryl Brahnam, Bill Kapralos, Lakhmi C. Jain

Bibliographic record

Venuenot available
Typebook
Languageen
FieldComputer Science
TopicVirtual Reality Applications and Impacts
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsPerspective (graphical)MetaverseField (mathematics)Engineering ethicsComputer scienceData scienceHuman–computer interactionSociologyEngineeringVirtual realityArtificial intelligence

Abstract

fetched live from OpenAlex

This book presents current innovative, alternative and creative approaches that challenge traditional mechanisms in and across disciplines and industries targeting societal impact. A common thread throughout the book is human-centered, uni and multi-modal strategies across the range of human technologies, including sensing and stimuli; virtual and augmented worlds; games for serious applications;accessibility; digital-ethics and more. Focusing on engaging, meaningful, and motivating activities that at the same time offer systemic information on human condition, performance and progress, the book is of interest to anyone seeking to gain insights into the field, be they students, teachers, practicing professionals, consultants, or family representatives. By offering a wider perspective, it addresses the need for a core text that evokes and provokes, engages and demands and stimulates and satisfies.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.022
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0030.004
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0220.005

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 head0.012
GPT teacher head0.297
Teacher spread0.285 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations8
Published2017
Admission routes1
Has abstractno

Explore more

Same topicVirtual Reality Applications and ImpactsFrench-language works237,207