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Record W4244552820 · doi:10.1109/tcyb.2021.3056864

IEEE Transactions on Cybernetics

2021· article· en· W4244552820 on OpenAlex
Eddie Past, Sr Tunstel, Andreas Nuernberger Vp-Cybernetics, Sam Kwong Vp-Finance, Ferat Sahin, Fei‐Yue Wang, Karen Panetta Vp-Organization, Planning Marik, Enrique Herrera‐Viedma, Adrian Stoica, Maria Pia Fanti, Keith W. Hipel, Okyay Kaynak, Róbert Kozma, Hideyuki Takagi, György Eigner, Karen Panetta, Ching‐Chih Tsai, Giancarlo Fortino, David Mendonça, Tadahiko Murata, Png Shi, Thomas Strasser, Daoyi Dong, Mariagrazia Dotoli, G Örgy Eigner, Владик Крейнович, Chaomei Chen, Susan Kathy, Land, K Liu, Kathleen Kramer, Ellen Randall, Toshiko Fukuda, Stephen Phillips, Educational Activities, Lawrence Hall, Maike Luiken, James Matthews, Roger Fujii, Katherine Duncan, Dalma Novak, Stephen Welby, Thomas Siegert, Business Administration, Julie Cozin, Corporate Governance, Donna Hourican, Jamie Moesch, Sophia Muirhead, Liesel Bell, Cherif Amirat, Karen Hawkins, Cecelia Jankowski, Geographic Activities, Steven Heffner

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

VenueIEEE Transactions on Cybernetics · 2021
Typearticle
Languageen
FieldComputer Science
TopicInternet of Things and AI
Canadian institutionsCanadian Standards Association
Fundersnot available
KeywordsCyberneticsComputer scienceCognitive sciencePsychologyArtificial intelligence

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.957
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.242
Teacher spread0.225 · 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