MétaCan
Menu
Back to cohort
Record W3190460002 · doi:10.1016/j.aml.2021.107566

Explicit <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="d1e229" altimg="si202.svg"> <mml:mi>p</mml:mi> </mml:math> -dependent convergence regions of Newton’s method for the matrix <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="d1e234" altimg="si202.svg"> <mml:mi>p</mml:mi> </mml:math> th root

2021· article· lv· W3190460002 on OpenAlexafffund
Di Lu, Chun‐Hua Guo

Bibliographic record

VenueApplied Mathematics Letters · 2021
Typearticle
Languagelv
FieldMathematics
TopicIterative Methods for Nonlinear Equations
Canadian institutionsUniversity of Regina
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsConvergence (economics)MathematicsEigenvalues and eigenvectorsComplex planeMatrix (chemical analysis)Newton's methodAlgorithmCombinatoricsApplied mathematicsMathematical analysisPhysicsNonlinear system

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.396
Threshold uncertainty score0.861

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.3960.273

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 head0.035
GPT teacher head0.297
Teacher spread0.263 · 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.

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

Citations2
Published2021
Admission routes2
Has abstractno

Explore more

Same venueApplied Mathematics LettersSame topicIterative Methods for Nonlinear EquationsFrench-language works237,207