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Record W2012874326 · doi:10.3141/1899-23

Real-Time Environmental Visualization with Web3D

2004· article· en· W2012874326 on OpenAlexaff
Bo Huang, Hongga Li, Magesh Chandramouli

Bibliographic record

VenueTransportation Research Record Journal of the Transportation Research Board · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicRemote Sensing and LiDAR Applications
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsComputer scienceInteractivityGeographic information systemThe InternetJavaVisualizationDatabaseData visualizationDistributed GISAM/FM/GISGIS applicationsWorld Wide WebData miningOperating systemRemote sensingGeography

Abstract

fetched live from OpenAlex

A project that uses a real-time web-based visualization approach for environmental modeling by integrating a geographic information system (GIS) with virtual reality modeling language and Java was explored. A new technique, the server push approach, is developed to “push” only up-to-date data from the remote server to the client and consequently reduce network traffic across the Internet. A fat client model is adopted to host the GIS environmental data model on the Internet. Online data hosting boosts interactivity, swift and transparent communication, user access, and cost-efficiency. These data can be analyzed online by using a GIS and the numerical functions embedded in Web3D-based Java applets. The spatially distributed GIS-based model used to generate data on catchment hydrology and runoff (the topography-based hydrological model; TOPMODEL) accepts incoming information and facilitates real-time simulation.

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)0.001
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: Software · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.002

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 head0.031
GPT teacher head0.330
Teacher spread0.299 · 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
GenreSoftware

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

Citations2
Published2004
Admission routes1
Has abstractyes

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