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Record W2054429493 · doi:10.1155/2014/726434

From Conventional Wireless Sensor Networks to Smart Grids

2014· article· en· W2054429493 on OpenAlexaffabout
Jin Jiang, Ataul Bari, Walid Saad, Shuai Li, Shiming Tian, Arunita Jaekel

Bibliographic record

VenueInternational Journal of Distributed Sensor Networks · 2014
Typearticle
Languageen
FieldEngineering
TopicEnergy Harvesting in Wireless Networks
Canadian institutionsUniversity of WindsorWestern University
Fundersnot available
KeywordsWindsorMiamiBeijingComputer scienceTelecommunicationsElectric powerElectrical engineeringChinaLibrary sciencePower (physics)EngineeringEnvironmental scienceArchaeologyGeography

Abstract

fetched live from OpenAlex

1 Department of Electrical and Computer Engineering, University of Western Ontario, London, ONT, Canada N6A 5B9 2 Electrical and Computer Engineering Department, University of Miami, Coral Gables, FL 33146, USA 3 Electrical and Computer Engineering Department, Stevens Institute of Technology, Hoboken, NJ 07307, USA 4China Electric Power Research Institute, No. 15, Xiaoying Road, Qinghe, Haidian, Beijing 100192, China 5 School of Computer Science, University of Windsor, Windsor, ONT, Canada N9B 3P4

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)0.002
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: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0010.005
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.007
GPT teacher head0.219
Teacher spread0.212 · 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

Citations1
Published2014
Admission routes2
Has abstractyes

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