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Record W3196548271 · doi:10.1109/wifs.2018.8630795

[Front cover]

2018· paratext· en· W3196548271 on OpenAlexfundno aff

Bibliographic record

Venuenot available
Typeparatext
Languageen
FieldComputer Science
TopicFace recognition and analysis
Canadian institutionsnot available
FundersUniversity at AlbanyRajamangala University of Technology SuvarnabhumiTechnische Universiteit DelftUniversidade de VigoUniversité de MontpellierUniversité de GenèveBeijing Jiaotong UniversityUniversity of Illinois at Urbana-ChampaignUniversity of Science and Technology of ChinaUniversity of Colorado Colorado SpringsSouth China University of TechnologyPrinceton UniversityUniversità degli Studi di PadovaSun Yat-sen UniversityCentre National de la Recherche ScientifiquePolitechnika WarszawskaDartmouth CollegeYork UniversityPolitecnico di TorinoDrexel UniversityHong Kong Baptist UniversityHarbin Institute of TechnologyUniversity of AlbertaUniversità degli Studi di SienaČeské Vysoké Učení Technické v Praze
KeywordsComputer scienceComputer securityAnonymityCover (algebra)BiometricsInformation securityClass (philosophy)Key (lock)CryptographyWorld Wide WebEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

The following topics are dealt with: image coding; cryptography; feature extraction; learning (artificial intelligence); neural nets; image forensics; image classification; face recognition; cameras; fingerprint identification.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.574
Threshold uncertainty score0.894

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.1060.680

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 head0.018
GPT teacher head0.259
Teacher spread0.241 · 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 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
Published2018
Admission routes1
Has abstractyes

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