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Record W2942909684 · doi:10.5539/mas.v13n5p130

Applications of Algebraic Geometry in Cryptography

2019· article· en· W2942909684 on OpenAlexvenueno aff
Nada Yassen Kasm, Zyiad Adrees Hamad

Bibliographic record

VenueModern Applied Science · 2019
Typearticle
Languageen
FieldComputer Science
TopicCryptography and Data Security
Canadian institutionsnot available
Fundersnot available
KeywordsWord (group theory)Computer scienceCryptographyEncryptionAlgebraic geometryLinguisticsAlgebraic numberApplied linguisticsAlgebra over a fieldMathematics educationMathematicsGeometryComputer securityPhilosophyPure mathematics

Abstract

fetched live from OpenAlex

One of the most important applications of algebraic geometry, known as linguistics, has been used in linguistics, military and diplomatic. It was said that the first to mobilize a comment between the army is the Pharaohs. He also mentioned that the Arabs have old attempts at encryption. The Chinese used many methods in conveying messages during war. Their intention was to get the wrong signals. This research is a general study on science (word) searching for several methods in English linguistics, a word of thanks and a message.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0020.006
Scholarly communication0.0030.005
Open science0.0000.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.002

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 head0.005
GPT teacher head0.220
Teacher spread0.215 · 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 designTheoretical or conceptual
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

Citations15
Published2019
Admission routes1
Has abstractyes

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