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Record W1980718426 · doi:10.3934/amc.2014.8.459

Smoothness testing of polynomials over finite fields

2014· article· en· W1980718426 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAdvances in Mathematics of Communications · 2014
Typearticle
Languageen
FieldComputer Science
TopicCryptography and Residue Arithmetic
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaCentre National de la Recherche Scientifique
KeywordsSmoothnessMathematicsDegree (music)Integer (computer science)Finite fieldFactorizationFunction (biology)Field (mathematics)Bernstein polynomialPoint (geometry)Applied mathematicsPure mathematicsDiscrete mathematicsMathematical analysisAlgorithmGeometry

Abstract

fetched live from OpenAlex

We present an analysis of Bernstein's batch integer smoothness testwhen applied to the case of polynomials over a finite field $\mathbb{F}_q.$ Wecompare the performance of our algorithm with the standard methodbased on distinct degree factorization from both an analytical and apractical point of view. Our results show that although the batchtest is asymptotically better as a function of the degree of thepolynomials to test for smoothness, it is unlikely to offersignificant practical improvements for cases of practical interest.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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: Methods · Consensus signal: none
Teacher disagreement score0.576
Threshold uncertainty score0.305

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.026
GPT teacher head0.303
Teacher spread0.278 · 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