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Record W7008608930

Classification of conservation laws of shallow-water
\nequations

2019· dissertation· en· W7008608930 on OpenAlexafffund

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2019
Typedissertation
Languageen
FieldMathematics
TopicNavier-Stokes equation solutions
Canadian institutionsMemorial University of Newfoundland
FundersMemorial University of Newfoundland
KeywordsConservation lawEquivalence (formal languages)Variable (mathematics)Algebraic numberGroup (periodic table)Calculus (dental)
DOInot available

Abstract

fetched live from OpenAlex

We carry out the complete classification of zero-order conservation laws of the classes
\nof one- and two-dimensional shallow-water equations with variable bottom topography.
\nWe also find the complete equivalence group for the one-dimensional case, using
\nthe direct method, and for the two-dimensional case, using the algebraic method.
\nUsing conservation-law characteristics, we find all inequivalent cases of bottom topographies
\n(up to the equivalence group), which give different spaces of conservation
\nlaws. Analogously, using additionally the method of furcate splitting, we solve the
\nclassification problem for conservation laws for the two-dimensional case.

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)0.002
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.447
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0010.001
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 head0.102
GPT teacher head0.331
Teacher spread0.228 · 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 teacher head, not a consensus.

Study designBench or experimental
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

Citations0
Published2019
Admission routes2
Has abstractyes

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