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Record W4383099037 · doi:10.1007/978-3-031-37189-9

Computer-Aided Architectural Design. INTERCONNECTIONS: Co-computing Beyond Boundaries

2023· book· en· W4383099037 on OpenAlexfundno aff

Bibliographic record

VenueCommunications in computer and information science · 2023
Typebook
Languageen
FieldEngineering
Topic3D Modeling in Geospatial Applications
Canadian institutionsnot available
FundersUniversità degli Studi di BresciaSyddansk UniversitetTechnion-Israel Institute of TechnologyUniversidade Federal de Juiz de ForaUniversidade do PortoTallinna TehnikaülikoolNottingham Trent Universityİzmir Yüksek Teknoloji EnstitüsüUniversity of Southern CaliforniaTrent UniversityUniversity of East LondonUniversity of ThessalyUniversité de LiègeTechnische Universiteit DelftAarhus UniversitetUniversidade do MinhoEidgenössische Technische Hochschule ZürichRMIT UniversityMassachusetts Institute of TechnologyTechnische Universität MünchenKU Leuven
KeywordsFutures contractComputer scienceArchitectural designArchitectural engineeringArchitectureSystems engineeringData scienceHuman–computer interactionEngineeringVisual artsBusinessArt

Abstract

fetched live from OpenAlex

CAAD Futures 2023 proceedings on support systems for design decisions, tools, methods and implementation of urban design, and rethinking spatial behavior.

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)0.002
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: none
Teacher disagreement score0.068
Threshold uncertainty score0.227

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0680.022

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 head0.034
GPT teacher head0.286
Teacher spread0.252 · 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

Citations12
Published2023
Admission routes1
Has abstractyes

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