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Record W58792425 · doi:10.22260/isarc2003/0041

Open Architecture for Site Layout Modeling

2003· article· en· W58792425 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

VenueProceedings of the ... ISARC · 2003
Typearticle
Languageen
FieldEngineering
TopicAdvanced Manufacturing and Logistics Optimization
Canadian institutionsConcordia University
Fundersnot available
KeywordsComputer scienceArchitecturePlan (archaeology)Object (grammar)Floor planSelection (genetic algorithm)Building information modelingSoftware engineeringEngineering drawingEngineeringArtificial intelligenceScheduling (production processes)

Abstract

fetched live from OpenAlex

ABSTRACT: This paper presents an overview of a computer-based site layout model and focuses primarily on the project setup phase. The developed model has four modules: user interface, database, project module, and layout module. Setting up the project in the proposed model is carried out by the project module, utilizing open architecture concept. The main advantage in the open architecture is to allow for the incorporation of user-defined objects if they are not readily available in the model. The objects required to define a site layout problem are clustered into three tires: 1) Site Objects, 2) Construction Objects, and 3) Constraint Objects. The model is implemented in a CAD environment using an object-based approach. The structure of each of the three tires is described, and the mechanism of object selection/creation for a site layout project is explained. The paper describes the components required to implement an open architecture for site layout object selection along with their respective environments. The developed model can be easily extended to similar applications such as floor plan design.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.829
Threshold uncertainty score0.305

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 head0.019
GPT teacher head0.231
Teacher spread0.212 · 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