MétaCan
Menu
Back to cohort
Record W7133046337

Quartic spline collocation methods for second-order two-point boundary value ODE problems

2007· dissertation· W7133046337 on OpenAlexfundno aff
Guohong Liu

Bibliographic record

VenueTSpace · 2007
Typedissertation
Language
FieldMathematics
TopicNumerical methods for differential equations
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsQuartic functionSingular boundary methodBoundary value problemCollocation (remote sensing)Collocation methodOrthogonal collocationOrdinary differential equation
DOInot available

Abstract

fetched live from OpenAlex

Collocation methods based on quartic splines are presented for second-order two-point boundary value problems. In addition to the boundary conditions specified by the problem, extra boundary conditions are introduced in order to uniquely determine the quartic spline approximation. The standard quartic spline collocation method gives fourth order bounds. Two optimal methods, namely the extrapolated (one-step) and the deferred-correction (two-step) methods, are formulated based on appropriate extra boundary conditions and an appropriate perturbation of the operators of the differential equation, boundary conditions and extra boundary conditions. The convergence analysis and error bounds are developed using a Green's functions approach. The analysis shows that the maximum discrete error is of sixth order, and the maximum global error is of fifth order for the optimal methods. The properties of the matrices arising from the optimal methods for a certain class of problems are studied. Non-optimal collocation methods based on different extra boundary conditions are also investigated. Problems with layers are also considered, and a grid refinement technique is presented. The theoretical behavior of the collocation methods is verified by numerical 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.

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)0.007
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.597
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.008
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.080
GPT teacher head0.517
Teacher spread0.437 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueTSpaceSame topicNumerical methods for differential equationsFrench-language works237,207