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Record W301273030

Sur la résolution efficace d'équations aux dérivées partielles en mécanique des fluides multiphasique et imagerie médicale

2014· dissertation· fr· W301273030 on OpenAlexfundno aff
Louis Le Tarnec

Bibliographic record

Venuetheses.fr (ABES) · 2014
Typedissertation
Languagefr
FieldComputer Science
TopicMedical Image Segmentation Techniques
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsHumanitiesPhysicsPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

This work is divided into four parts. The first three parts, as a common base, aim at adapting a finite volume scheme (VFFC) to various situations, in order to get a better efficiency for the numerical simulation of complex flows. The first part deals with the efficient numerical simulation of a falling block of liquid in a gas pocket, and proposes a new model to combine previous work for associating precision of results and computational efficiency. The second part aims at the establishment of a general AMR (Adaptive Mesh Refinement) scheme for resolution by finite volumes of non-conservative systems. The purpose of the third part is the dynamic coupling of two models representing more or less finely a given physical system. Finally, in any other area where the efficiency of solving partial differential equations is of great importance too, the fourth part deals with the problem of optical flow in imaging - i.e. the research of a displacement field from several successive images - and deepens an existing method (Horn and Schunck method) from a practical and theoretical perspective.

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)0.004
metaresearch head score (Gemma)0.007
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: Methods · Consensus signal: none
Teacher disagreement score0.726
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.037
GPT teacher head0.344
Teacher spread0.306 · 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
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
Published2014
Admission routes1
Has abstractyes

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Same venuetheses.fr (ABES)Same topicMedical Image Segmentation TechniquesFrench-language works237,207