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Record W4411181591 · doi:10.62754/ais.v6i2.136

The Ghosts of Architecture Point Clouds, Affect and Collaged Hauntopias

2025· article· en· W4411181591 on OpenAlexaboutno aff
Nic Clear, Hyun Jun Park

Bibliographic record

VenueArchitecture Image Studies · 2025
Typearticle
Languageen
FieldEngineering
TopicArchitecture and Computational Design
Canadian institutionsnot available
Fundersnot available
KeywordsAffect (linguistics)ArchitecturePoint (geometry)PsychologyArtCommunicationMathematicsVisual artsGeometry

Abstract

fetched live from OpenAlex

Clear+Park (C+P) use 3D laser scanning to create works that operate across architecture, installation, and media arts. C+P capture, edit and manipulate point-cloud data to document spaces, create speculative projects and spatial propositions; creating digital images and animations that engage with and respond to specific site narratives. In their work, C+P create complex assemblages that combine 3D rendering and post-production effects to create spatial collages that operate between the actual and the virtual. Using the veracity and verisimilitude of the scans opens a powerful opportunity to critique traditional forms of representation where conceptions of authenticity and specificity of place can be radically questioned. In the same way, the images of architectural photography do not simply reflect the inherent qualities of the architecture but actively construct those qualities. Author Biographies Nic Clear, Professor of Architecture & Dean of School of Arts and Humanities, University of Huddersfield Professor Nic Clear is a qualified architect, writer and curator. He is Professor of Architecture and Dean of the School of Arts and Humanities at the University of Huddersfield. He was a Professor of Architecture and Head of the Department of Architecture and Landscape at the University of Greenwich, having previously taught at the Bartlett School of Architecture for over 20 years. In 2015, he was the Inaugural Professor for Research in Visionary Cities at the Institute of Fine Arts in Vienna, and has taught in the UK, Europe, the US and Canada. Hyun Jun Park, Course Director Postgraduate Architecture, Leeds Beckett University Hyun Jun Park is a practitioner, writer, curator, fellow of the Royal Society of Arts and Course Director for Postgraduate Architecture at the Leeds School of Architecture, Leeds Beckett University. Prior to this, he was Course Leader for the Master of Architecture at the University of Huddersfield and taught postgraduate M.Arch design studio at the University of Greenwich. Before he came to the UK, he was an associate architect at SAMOO Architects & Engineers (SAMSUNG Corp), Seoul, Korea. He was awarded M.Arch by the Bartlett School of Architecture and finished his BA and first master’s degree at Hongik University, Seoul, Korea. Clear + ParkClear+Park use 3D laser scanning to create multidisciplinary works that operate across architecture, installation, and media arts. Clear+Park use 3D scanning to capture spaces and create spatial representations and narratives that engage with, and respond to specific site histories and spatial practices. Through their research Clear+Park explore ways in which architects and artists can reproduce, develop, manipulate, and represent spaces using advanced digital technology in ways that engage with non-specialist audiences.

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)0.003
metaresearch head score (Gemma)0.007
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: Other · Consensus signal: Other
Teacher disagreement score0.013
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0130.041
Scholarly communication0.0110.008
Open science0.0010.010
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.006
GPT teacher head0.250
Teacher spread0.244 · 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
GenreOther

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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