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Record W4248917891 · doi:10.1109/tifs.2014.2323186

IEEE Transactions on Information Forensics and Security publication information

2014· article· en· W4248917891 on OpenAlexaff
C.‐C. Jay Kuo, Ming H. Hsieh, Mostafa Abdalla, Patrizio Campisi, Linying Chen, Sen-ching S. Cheung, Teddy Furon, S. Goldenstein, Y.-W. Peter Hong, Jingyi Huang, Ramesh Karri, Hitoshi Kiya, Alex C. Kot, Jonathan Li, Sébastien Marcel, Giuseppe Persiano, Sagar S. Rane, Kui Ren, Roberto De Marca, Howard Michel, Marko Delimar, John Barr, Peter Staecker, Ralph Ford, Karen Bartleson, Jacek M. Zurada, Gary Blank, Dr Prendergast, Thomas Siegert, Business Administration, Matthew Loeb, Douglas Gorham, Eileen Lach, Corporate Compliance, Shannon Johnston, Ieee-Usa Chris Brantley, Alexander Pasik, Information Technology, Patrick Mahoney, Fran Zappulla, Peter Tuohy, Jeffrey Cichocki

Bibliographic record

VenueIEEE Transactions on Information Forensics and Security · 2014
Typearticle
Languageen
FieldComputer Science
TopicDigital and Cyber Forensics
Canadian institutionsCanadian Standards AssociationUniversity of Toronto
Fundersnot available
KeywordsComputer scienceComputer securityInformation securityComputer forensicsNetwork forensicsInternet privacyWorld Wide WebDigital forensics

Abstract

fetched live from OpenAlex

The Signal Processing Society is an organization, within the framework of the IEEE, of members with principal professional interest in the technology of transmission, recording, reproduction, processing, and measurement of speech; other audio-frequency waves and other signals by digital electronic, electrical, acoustic, mechanical, and optical means; the components and systems to accomplish these and related aims; and the environmental, psychological, and physiological factors of these technologies. All members of the IEEE are eligible for membership in the Society and will receive this TRANSACTIONS upon payment of the annual Society membership fee of $35.00 plus an annual subscription fee of $163.00.

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 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), Scholarly communication
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.978
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.021
Open science0.0000.000
Research integrity0.0000.001
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 head0.007
GPT teacher head0.197
Teacher spread0.190 · 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; both teacher heads agree on what is shown here.

Study designOther design
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

Citations0
Published2014
Admission routes1
Has abstractyes

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