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Record W2121079060 · doi:10.7202/022761ar

Modèles morphodynamiques de segmentation spatiale

2005· article· fr· W2121079060 on OpenAlexvenueno aff
Jean Petitot

Bibliographic record

VenueCahiers de géographie du Québec · 2005
Typearticle
Languagefr
FieldComputer Science
TopicImage Retrieval and Classification Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesGeographyArt

Abstract

fetched live from OpenAlex

Partant de la phénoménologie de la perception et de la conception structurale-dynamique des discontinuités géographiques dans les travaux de Gilles Ritchot et de Gaëtan Desmarais sur la forme urbaine, l'article aborde le problème fondamental de la segmentation spatiale et de l'émergence des discontinuités qualitatives dans des espaces substrats. Il montre comment le traitement morphologique des images permet de comprendre les mécanismes d'individuation de domaines spatiaux localisés. Ces mécanismes peuvent être adéquatement modélisés à l'aide de formalismes de type morphodynamique, en particulier les modèles variationnels de segmentation spatiale (Mumford et Shah, 1989) et les modèles multi-échelles régis par des équations de diffusion non-linéaires anisotropes (Malik et Perona, Morel). Des exemples en imagerie géographique sont utilisés.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.760
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.003
Scholarly communication0.0000.001
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 head0.012
GPT teacher head0.232
Teacher spread0.220 · 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 designOther design
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

Citations1
Published2005
Admission routes1
Has abstractyes

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