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Record W4285091417 · doi:10.3390/land11071055

The Future of City Squares: Robotics in the Urban Design of Tomorrow

2022· article· en· W4285091417 on OpenAlexaff
Karolina Dąbrowska-Żółtak, J Wójtowicz, Stefan Wrona

Bibliographic record

VenueLand · 2022
Typearticle
Languageen
FieldEngineering
TopicArchitecture and Computational Design
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMechatronicsArchitectureSpace (punctuation)Order (exchange)Public spaceRoboticsUrban designComputer scienceEngineering managementUrban planningArtificial intelligenceKnowledge managementEngineeringArchitectural engineeringHuman–computer interactionSystems engineeringManagement scienceRobotBusinessCivil engineeringGeography

Abstract

fetched live from OpenAlex

Technological development generates social changes while providing new tools that can be implemented in the fields of architecture and urban design. It creates the need to enrich architects’ competencies with knowledge and experience, enabling the conscious use of technology in designing future functional solutions for responsive space and the optimization of accessibility for various groups of users. This paper presents a teaching method developed to study the integration of architecture, urban planning and mechatronics to create a dynamic common space, responding to changing user needs and environmental conditions. Four experimental projects for a chosen public space were designed by students in order to investigate research by design and as an agenda for further design research. In the final part of the article, we present predictions for the future development of kinetic and responsive architecture in public spaces, including potential opportunities and challenges.

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 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 score0.618
Threshold uncertainty score0.080

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.010
GPT teacher head0.194
Teacher spread0.184 · 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 designSimulation or modeling
Domainnot available
GenreEmpirical

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
Published2022
Admission routes1
Has abstractyes

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