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Record W2151891161 · doi:10.1109/access.2015.2498288

Cybermatics: A Holistic Field for Systematic Study of Cyber-Enabled New Worlds

2015· article· en· W2151891161 on OpenAlex

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 Access · 2015
Typearticle
Languageen
FieldComputer Science
TopicCellular Automata and Applications
Canadian institutionsSt. Francis Xavier University
FundersFundamental Research Funds for the Central UniversitiesJapan Society for the Promotion of ScienceNational Natural Science Foundation of China
KeywordsCyberspaceInformatizationField (mathematics)Computer scienceCyber-physical systemData scienceWorld Wide WebThe InternetMathematics

Abstract

fetched live from OpenAlex

Following the two trends of computerization and informatization, another emerging trend is cyberization in which numerous and various cyber entities in cyberspace will exist in cyber-enabled worlds, including the cyber world and cyber-conjugated physical, social, and mental worlds. Computer science and information science, as holistic fields, have, respectively, played important roles in computerization and informatization. Similarly, it is necessary for there to be a corresponding field for cyberization. Cybermatics is proposed as such a holistic field for the systematic study of cyber entities in cyberspace and cyber world, and their properties, functions, and conjugations with entities in conventional spaces/worlds. This paper sets out to explain the necessity and rationale for, and significance of, the proposed field of Cybermatics, what it is and what it encompasses, and how it is related to other fields and areas.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.868
Threshold uncertainty score0.384

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 communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.102
GPT teacher head0.361
Teacher spread0.259 · 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