MétaCan
Menu
Back to cohort
Record W4232560372 · doi:10.1002/9781119970422.ch1

Introduction

2011· other· en· W4232560372 on OpenAlexaff
Mohammad S. Obaidat, Isaac Woungang

Bibliographic record

Venuenot available
Typeother
Languageen
FieldComputer Science
TopicContext-Aware Activity Recognition Systems
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsUbiquitous computingComputer scienceContext-aware pervasive systemsMobile computingMobile deviceWirelessEnd-user computingThe InternetMultimediaWireless sensor networkWireless networkUbiquitous robotHuman–computer interactionUtility computingTelecommunicationsWorld Wide WebComputer networkCloud computingOperating systemArtificial intelligence

Abstract

fetched live from OpenAlex

Ubiquitous computing (nowadays also referred to as pervasive computing) was a revolutionary paradigm and technology introduced nearly a decade ago in a seminal 1991 paper by MarkWeiser in these terms: ‘the method of enhancing computer use by making many computers available throughout the physical environment, but making them invisible to the user’, based upon the following vision:‘The most profound technologies are those that disappear. Pervasive computing is aiming at improving significantly the human experience and quality of life without explicit awareness of the underlying computing technologies and communications. In recent years, there have been a number of research developments and technologies that have emerged in areas such as Internet technologies, mobile and distributed computing, handheld devices, computer hardware, wireless communication networks, embedded systems and computing, wireless sensor networks, software agents, humancomputer interfaces, and the like. These advances have led to the emergence of several pervasive computing and networking applications. Controlled Vocabulary Terms mobile handsets; ubiquitous computing

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.503
Threshold uncertainty score0.718

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0070.006
Open science0.0020.004
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.4970.334

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 head0.025
GPT teacher head0.224
Teacher spread0.200 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2011
Admission routes1
Has abstractyes

Explore more

Same topicContext-Aware Activity Recognition SystemsFrench-language works237,207