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Record W1985812000 · doi:10.1109/iot.2012.6402318

IoT mashups with the WoTKit

2012· article· en· W1985812000 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicContext-Aware Activity Recognition Systems
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMashupInternet of ThingsComputer scienceKey (lock)World Wide WebWeb of ThingsWeb applicationThe InternetWeb developmentComputer security

Abstract

fetched live from OpenAlex

Toward reducing barriers for developing applications for the Internet of Things, researchers have connected things to the web enabling the development of IoT mashups. While establishing a Web of Things for mashup development has been an important step forward, we believe that web-centric IoT toolkits have the potential to increase the use of Internet-enabled things further by increasing the pool of developers and applications that can take advantage of the connected physical world. In this paper we derive several key requirements for IoT mashup toolkits based on existing systems, past research and our experience with an IoT mashup toolkit called the Web of Things Toolkit (WoTKit). Unlike other systems, the WoTKit aims to address key requirements for IoT mashup developers in one system. From this experience we derive key lessons learned for the community toward improving toolkits for developing IoT mashups.

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.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.932
Threshold uncertainty score1.000

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)0.0000.001

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 head0.219
Teacher spread0.198 · 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

Quick stats

Citations100
Published2012
Admission routes1
Has abstractyes

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