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Record W2138320903 · doi:10.11575/prism/30586

Bounding the Nullities of Random Block Hankel Matrices: An Alternative Approach

2005· article· en· W2138320903 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.

Bibliographic record

VenuePRISM (University of Calgary) · 2005
Typearticle
Languageen
FieldComputer Science
TopicMatrix Theory and Algorithms
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMathematicsBounding overwatchLanczos resamplingBlock (permutation group theory)Rank (graph theory)Hankel matrixAlgebra over a fieldApplied mathematicsCombinatoricsPure mathematicsComputer scienceMathematical analysis

Abstract

fetched live from OpenAlex

Bounds are developed for the probability that various randomly generated block Hankel matrices are rank-deficient. These bounds are potentially of use to analyze the efficiency and reliability of various randomized block Wiedemann and block Lanczos algorithms, that are either currently under development or now in use, when these are applied to solve systems of linear equations and sample from the null space of matrices over small finite fields. The bounds that are presented here resemble ones that have previously been obtained using other arguments or that could likely be obtained by straightforward extensions of arguments that have recently been presented. The method used to obtain these bounds in this report is rather different and may be of some interest in its own right: It relies only on estimates of the number of irreducible polynomials of a given degree over a finite field and on elementary linear algebra.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.973
Threshold uncertainty score0.342

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 communication0.0000.001
Open science0.0010.000
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 head0.013
GPT teacher head0.203
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