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Record W4308197436 · doi:10.32920/21502173.v1

Designing of an Algebraic Signature Analyzer for Mixed-Signal Systems

2022· preprint· en· W4308197436 on OpenAlexaff
Vadim Geurkov, Lev Kirischian

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldComputer Science
TopicVLSI and Analog Circuit Testing
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsSignature (topology)Algebraic numberSpectrum analyzerComputer scienceCoding (social sciences)CryptographyAlgorithmSIGNAL (programming language)Carry (investment)Scheme (mathematics)Theoretical computer scienceArithmeticMathematicsStatisticsProgramming languageTelecommunications

Abstract

fetched live from OpenAlex

<p>In this paper, we propose a novel approach to designing an algebraic signature analyzer that can be employed for mixed-signal systems testing. Due to its algebraic nature, the analyzer does not contain carry propagating circuitry. This helps to improve its error immunity, as well as performance. The proposed scheme can also be used in arithmetic/algebraic error-control coding and cryptography.</p>

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.951
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.031
GPT teacher head0.267
Teacher spread0.236 · 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 teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreMethods

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
Published2022
Admission routes1
Has abstractyes

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