MétaCan
Menu
Back to cohort
Record W2333471706 · doi:10.3934/cpaa.2012.11.1839

Collocation methods for differential equations with piecewise linear delays

2012· article· en· W2333471706 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

VenueCommunications on Pure &amp Applied Analysis · 2012
Typearticle
Languageen
FieldMathematics
TopicNumerical methods for differential equations
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsSuperconvergencePiecewiseCollocation (remote sensing)Orthogonal collocationCollocation methodConstant (computer programming)Piecewise linear functionMathematicsApplied mathematicsNumerical analysisMathematical analysisDifferential equationComputer scienceOrdinary differential equationFinite element methodPhysics

Abstract

fetched live from OpenAlex

After analyzing the regularity of solutions to delay differentialequations (DDEs) with piecewise continuous (linear) non-vanishingdelays, we describe collocation schemes using continuous piecewisepolynomials for their numerical solution. We show that for carefullydesigned meshes these collocation solutions exhibit optimal ordersof global and local superconvergence analogous to the ones for DDEswith constant delays. Numerical experiments illustrate thetheoretical superconvergence results.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.403
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.171
GPT teacher head0.463
Teacher spread0.292 · 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