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Record W4206969593 · doi:10.1109/lwc.2021.3105859

IEEE Wireless Communications Letters

2021· article· en· W4206969593 on OpenAlexaff
Michele Zorzi, Kit Kai, J Milizzo, Chan‐Byoung Chae, Harpreet S. Dhillon, Ioannis Krikidis, Daniel K. C. So, Koichi Adachi, George C. Alexandropoulos, Ahmad Alsharoa, Mohamad Assaad, Vimal Bhatia, Zheng Chang, Honglin Chen, Jung-Chieh Chen, Wenchi Cheng, Jinho Choi, Daniel Benevides da Costa, Susan Kathy, Land, Kun Liu, Kathleen Kramer, Ellen Randall, Toshio Fukuda, Stephen Phillips, Educational Activities, Lawrence Hall, Maike Luiken, James Matthews, Roger Fujii, Katherine Duncan, Sergio Benedetto, Stephen Welby, Thomas Siegert, Donna Hourican, Jamie Moesch, Sophia Muirhead, Chris Brantley, Ieee-Usa Cherif, Karen Hawkins, Cecelia Design, Geographic Jankowski, Steven Activities

Bibliographic record

VenueIEEE Wireless Communications Letters · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsCanadian Standards Association
Fundersnot available
KeywordsComputer scienceWirelessComputer networkTelecommunications

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.296
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0030.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.009

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 head0.072
GPT teacher head0.249
Teacher spread0.176 · 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 teacher head, not a consensus.

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

Citations1
Published2021
Admission routes1
Has abstractno

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