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Record W2079320154 · doi:10.1145/500141.500257

vCOM

2001· article· en· W2079320154 on OpenAlexaff
Xiaojun Shen, Saeid Nourian, Isabelle Hertanto, Nicolas D. Georganas

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldDecision Sciences
TopicSimulation Techniques and Applications
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsShopping mallComputer scienceSimple (philosophy)VendorArchitectureInterface (matter)User interfaceHuman–computer interactionWorld Wide WebOperating systemAdvertising

Abstract

fetched live from OpenAlex

Existing electronic commerce applications only provide the user with a relatively simple browser-based interface to access products. Buyers, however, are not provided with the same shopping experience, as they would have in an actual store or shopping mall. With the creation of a virtual shopping mall, simulations of most of the actual shopping environments and user interactions can be achieved. The virtual mall brings together the services and inventories of various vendors. Users can either navigate through the vendors, adding items into a virtual shopping cart, or perform intelligent searches through "user and vendor agents". The electronic mall prototype also allows the user to communicate with an "intelligent assistant" (IA) using simple voice commands. This assistant interacts with the shopper using voice synthesis and helps him or her use the interface to navigate efficiently in the mall. Real-time interactions among entities in the virtual environment are implemented over the Run Time Infrastructure of the High Level Architecture (RTI/HLA), an OMG and IEEE standard for distributed simulations and modeling developed by the US Department of Defense.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.870
Threshold uncertainty score0.999

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)0.0070.002

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 head0.319
GPT teacher head0.519
Teacher spread0.201 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations1
Published2001
Admission routes1
Has abstractyes

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