MétaCan
Menu
Back to cohort
Record W7015899733

Voice and Multimodal Access to AEC Project Information

2003· article· en· W7015899733 on OpenAlexfundvenueno aff

Bibliographic record

VenueNPARC · 2003
Typearticle
Languageen
FieldComputer Science
TopicSpeech and dialogue systems
Canadian institutionsnot available
FundersNational Research Council CanadaStanford Bio-XIndustry Canada
KeywordsLaptopMobile deviceMobile WebWeb applicationMobile telephonyMobile technologyWirelessMobile computing
DOInot available

Abstract

fetched live from OpenAlex

With current developments in information and communication technology, we are rapidly moving away from the Desktop and Laptop Web paradigms towards the Mobile Web paradigm, where mobile smart devices such as Smart phone, Pocket PC, PDA, hybrid devices (phone-enabled Pocket PC), and wear-able computers will become powerful enough to replace laptop computers in the field. The availability of real time, complete information exchange with the project information repository is critical for decision making in the construction field, as information frequently has to be transmitted to and received from the project repository right on site. Whereas construction sites are often established for limited periods of time in locations where wired telecommunication infrastructure is often unavailable or limited. Therefore, it becomes important to establish a framework for augmenting the existing integrated project repository environment with mo-bile wireless devices. Mobile workers on a construction site will be able to use smart mobile devices to communicate with the project information repository in real time thus enabling timely and informed decision making on the project. This paper discusses the advantages of using VoiceXML technology for mobile industrial applications, presents a pilot industrial application of voice technology, and underlines the direction of future research in the area of mobile multimodal communication of AEC project information.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.751
Threshold uncertainty score0.295

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 communication0.0000.001
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 head0.021
GPT teacher head0.274
Teacher spread0.253 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2003
Admission routes2
Has abstractyes

Explore more

Same venueNPARCSame topicSpeech and dialogue systemsFrench-language works237,207