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Record W4410942750 · doi:10.1080/24751448.2025.2476882

Indoor Video Mapping to Measure Users’ Satisfaction in Third-Place Environments

2025· article· en· W4410942750 on OpenAlexaff
Habib Shahhoseini, Ziba Mousapour, Paniz Mousavi Samimi

Bibliographic record

VenueTechnology|Architecture + Design · 2025
Typearticle
Languageen
FieldComputer Science
TopicVirtual Reality Applications and Impacts
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMeasure (data warehouse)Computer scienceDatabase

Abstract

fetched live from OpenAlex

The study evaluates users’ satisfaction in third-place environments using Narrative, Artistic, and Neutral Indoor Video Mapping (IVM). The Third Place is a public space that provides a suitable environment for people’s social interactions outside their home (first place) and workplace (second place). We also studied the effects of architectural style preferences on the impact of IVM types on users’ satisfaction. Collected data from 368 questionnaires and nine displayed IVMs were analyzed. The results demonstrate a significant correlation between IVM and users’ satisfaction; Artistic and Narrative IVM, by affecting the environment’s attractiveness, and Neutral IVM, by affecting the lighting perception, enhances users’ satisfaction in third places. Also, there is a significant difference between the IVM preference and users’ satisfaction with traditional and industrial architectural style preferences.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.839
Threshold uncertainty score0.929

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.024
GPT teacher head0.254
Teacher spread0.229 · 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 designOther design
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

Citations0
Published2025
Admission routes1
Has abstractyes

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