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Record W4232602283 · doi:10.1109/tmbmc.2020.3006770

IEEE Communications Society

2020· article· en· W4232602283 on OpenAlexaff
Chan‐Byoung Chae, Christina Tang-Bernas, Sasitharan Balasubramaniam, Jaewon Choi, Chung‐Kwang Chou, Yaohua Deng, Faramarz Fekri, Alin Grama, Pragati Grover, Weisi Guo, Werner Haselmayr, Vaidyanathan Krishnamurthy, Tadashi Nakano, Masoumeh Nasiri‐Kenari, Adam Noel, Haris Vikalo, Ningchen Yang, Baki Berkay Yilmaz, Toshio Fukuda, Susan Kathy, Land, Kathleen Kramer, Joseph Lillie, Márcio das Chagas Moura, Stephen Phillips, Kripasindhu Sarkar, Kukjin Chun, Robert Fish, Kazuhiro Kosuge, James Conrad, Vijay K. Bhargava, Stephen Welby, Thomas Siegert, Business Administration, Cherif Amirat, Julie Cozin, Karen Hawkins, Donna Hourican, Cecelia Jankowski, Geographic Activities, Jamie Moesch, Sophia Muirhead, Konstantinos Karachalios, Mary Ward-Callan

Bibliographic record

VenueIEEE Transactions on Molecular Biological and Multi-Scale Communications · 2020
Typearticle
Languageen
FieldComputer Science
TopicHistory of Computing Technologies
Canadian institutionsCanadian Standards Association
Fundersnot available
KeywordsTelecommunicationsComputer sciencePolitical science

Abstract

fetched live from OpenAlex

MULTI-SCALE COMMUNICATIONS JOURNAL contains papers pertaining to analog and digital signal processing and modulation, audio and video encoding techniques, the theory and design of transmitters, receivers, and repeaters for communications via optical and sonic media, the design and analysis of computer communications systems, and the development of communication software. Contributions of theory enhancing the understanding of communication systems and techniques are included, as are discussions of the social implications of the development of communication technology. For membership and subscription information and pricing, please visit www.

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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.269
Threshold uncertainty score0.900

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.2690.313

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 head0.095
GPT teacher head0.292
Teacher spread0.197 · 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
GenreOther

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
Published2020
Admission routes1
Has abstractyes

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Same venueIEEE Transactions on Molecular Biological and Multi-Scale CommunicationsSame topicHistory of Computing TechnologiesFrench-language works237,207