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Record W2053564579 · doi:10.4171/ifb/86

On level-set approach to motion of manifolds of arbitrary codimension

2003· article· en· W2053564579 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

VenueInterfaces and Free Boundaries Mathematical Analysis Computation and Applications · 2003
Typearticle
Languageen
FieldMathematics
TopicMathematical Dynamics and Fractals
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCodimensionLevel set (data structures)MathematicsMotion (physics)Set (abstract data type)Function (biology)Manifold (fluid mechanics)CurvatureMathematical analysisLevel set methodDifferential topologyZero (linguistics)Mean curvatureDifferential (mechanical device)Pure mathematicsGeometryComputer scienceRicci-flat manifoldPhysicsClassical mechanicsImage (mathematics)Artificial intelligence

Abstract

fetched live from OpenAlex

Ambrosio and Soner We investigate for what (other) normal velocities, and how, the level-set methods can be used to treat motion of manifolds of arbitrary codimension by the given velocity. Two variants of the level-set approach are studied. One uses the properties of the distance function to describe the motion. In the other one, the moving manifolds are represented as a zero-level set of a solution to a parabolic differential equation. Necessary conditions and sufficient conditions for these approaches to be applicable are given. The motion of curves in R n , by a velocity that is parallel to the normal vector, is studied in greater detail and the velocities to which the level-set methods apply are partially classified.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.711
Threshold uncertainty score0.550

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.051
GPT teacher head0.307
Teacher spread0.257 · 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