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Record W2078313061 · doi:10.1145/2505403.2505411

SWE 2012 workshop report

2013· article· en· W2078313061 on OpenAlexaff
Steve Liang, Yong Liu, Yan Xu

Bibliographic record

VenueSIGSPATIAL Special · 2013
Typearticle
Languageen
FieldComputer Science
TopicEnergy Efficient Wireless Sensor Networks
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSensor webWorld Wide WebComputer scienceWeb siteWeb applicationState (computer science)Data scienceThe InternetTelecommunicationsKey distribution in wireless sensor networksWireless

Abstract

fetched live from OpenAlex

The international Sensor Web Enablement (SWE) workshop series bring together sensor web experts to present and discuss the latest ideas about the broadly defined Sensor Web, its infrastructure, relevant algorithms and new innovative applications. The SWE workshops also serve as a forum for Sensor Web users, developers and researchers to debate and discuss the current state-of-the-art and to shape the future of the Sensor Web. SWE workshops especially welcome real-world results and deployments of the sensor web systems.

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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.868
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 communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.010
GPT teacher head0.219
Teacher spread0.209 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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