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Enhancing efficiency and user-centricity in architectural remodeling: A comprehensive system design for structural renovation

2024· article· en· W4396242884 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueApplied and Computational Engineering · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsMcGill University
Fundersnot available
KeywordsArchitectural engineeringArchitectural designBusinessComputer scienceProcess managementEngineeringSystems engineeringArchitectureGeography

Abstract

fetched live from OpenAlex

The home renovation industry has witnessed remarkable growth, driven by shifts in lifestyle necessitating adjustments in living spaces. This paper addresses critical gaps in the domain of architectural remodeling, with a particular focus on improving efficiency, referenceability, and user-centricity in structural remodeling. This research introduces a system design tailored for structural remodeling within house renovation, catering to both comprehensive and partial projects to facilitate the creation of structurally viable renovation options and optimizing them to align precisely with user requirements. The proposed system's accessibility and consideration of architectural factors set it apart. While offering substantial benefits, the system has limitations, such as the exclusion of interior furnishing styles in output solutions. In conclusion, contributes to the improvement of remodeling projects and offers a promising approach, particularly in the early stages of these endeavors.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.518
Threshold uncertainty score0.327

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 head0.044
GPT teacher head0.218
Teacher spread0.174 · 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