MétaCan
Menu
Back to cohort

Linear Scheduling and 4D Visualization

2008· article· en· W2100176012 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

VenueJournal of Computing in Civil Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCADComputer scienceScheduleScheduling (production processes)SoftwareVisualizationComputer Aided DesignSoftware engineeringEngineering drawingIndustrial engineeringSystems engineeringData miningEngineeringProgramming language

Abstract

fetched live from OpenAlex

Described in this paper is a novel approach to four-dimensional (4D) computer-aided design (CAD). It involves a two-way symbiotic relationship between three-dimensional (3D) CAD software and a software implementation of linear planning that includes the ability to define a project product model and associate it with the process model. Strengths of the approach include the ability to readily modify construction sequences and examine their consequences using 4D CAD, and the ability to treat very large scale projects marked by significant repetition of their components. By building on a shared image of the project product model from both a design and construction perspective, the CAD model can be structured in a way that facilitates communication with the scheduling software and vice versa. Various challenges involved in making the 2-way process work are described, including consistency of product representation in the CAD and scheduling models, and the need to group CAD components at different levels of detail and locations to reflect the kinds of aggregation found in schedule representations of a project. The benefits of the approach include the ease with which different scheduling strategies can be explored and visualized, the links between 3D objects and activities can be maintained, and the completeness of the product model representations can be validated. A case study is used to illustrate the approach adopted and the challenges involved.

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: Empirical
Teacher disagreement score0.372
Threshold uncertainty score0.348

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 head0.009
GPT teacher head0.217
Teacher spread0.208 · 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