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Record W2140159737 · doi:10.1109/aiccsa.2003.1227471

Building wireless Internet services: state of the art

2004· article· en· W2140159737 on OpenAlexaff
Qusay H. Mahmoud

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicMobile Agent-Based Network Management
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsComputer scienceMobile deviceThe InternetWirelessWireless networkComputer networkMobile computingMobile WebMultimediaBandwidth (computing)TelecommunicationsMobile technologyWorld Wide Web

Abstract

fetched live from OpenAlex

Summary form only given. Most Internet technologies have been designed for desktop and large computers running on reliable networks with relatively high bandwidth. Handheld wireless devices (or mobile devices), however, have a more constrained computing environment compared to desktop computers. Mobile devices tend to have less memory, less powerful CPUs, different input devices, and smaller displays. Further, wireless networks have less bandwidth and more latency compared to wired computer networks. Several solutions have been proposed to address these constraints, but as the wireless Internet market is moving at fast pace; new devices and technologies are always on the horizon and developers are faced with the challenge of learning about these devices, the technologies and development environments available that can be used to develop applications for these mobile devices. We present an overview of the three widely used technologies for building wireless Internet services, followed by a comparison of the different technologies.

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)0.003
metaresearch head score (Gemma)0.003
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: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.006
Science and technology studies0.0010.001
Scholarly communication0.0060.010
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0200.010

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 head0.007
GPT teacher head0.209
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; 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
GenreReview

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

Citations0
Published2004
Admission routes1
Has abstractyes

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