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Record W2353604318

Study on Method of Constructing Road Integrated 3D Model

2003· article· en· W2353604318 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSimulation and Modeling Applications
Canadian institutionsCAE (Canada)
Fundersnot available
KeywordsDelaunay triangulationTerrainRoad surfaceComputer science3D modelingConstraint (computer-aided design)VisualizationKey (lock)TriangulationTransport engineeringEngineeringComputer visionCivil engineeringArtificial intelligenceGeographyAlgorithmCartography
DOInot available

Abstract

fetched live from OpenAlex

The key to realize the 3D road visualization is to establish an integrated road and ground 3D model. The paper analyzes the method of establishing the 3D road model. In order to overcome its existing insufficiencies, the paper proposes a method of integrating the road surface design model and the ground surface design model. On the basis of the theory of inserting points of the constrained Delaunay triangulation and the constraint segments in CDT, the paper solves the problem of erasing the ground surface points that are located on the road design region. With the integrated road model we can browse the 3D road among the ground scenery and access the 3D stereo route and the harmony with the surrounding terrain. 

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 score0.594
Threshold uncertainty score0.208

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 head0.058
GPT teacher head0.336
Teacher spread0.279 · 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

Quick stats

Citations3
Published2003
Admission routes1
Has abstractyes

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