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Record W2073517351 · doi:10.3166/isi.17.4.17-47

Approche pour un meilleur alignement des processus métiers. De la modélisation à l'implémentation

2012· article· fr· W2073517351 on OpenAlexvenueno aff
Jean-Stéphane Ulmer, Jean-Pierre Belaud, Jean-Marc Le Lann

Bibliographic record

VenueIngénierie des systèmes d information · 2012
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicBusiness Process Modeling and Analysis
Canadian institutionsnot available
FundersAgence Nationale de la Recherche
KeywordsComputer science

Abstract

fetched live from OpenAlex

Une entreprise doit être capable de décrire et de demeurer réactive face à un évènement endogène ou exogène. Une telle flexibilité peut s'obtenir par la gestion des processus d’entreprise. Lors d'une telle démarche, différentes transformations interviennent sur les modèles de processus développés par l'analyste métier et l’expert en technologies de l'information (TI). Un non-alignement se crée entre ces modèles hétérogènes lors de leurs manipulations : il s'agit du "fossé métier-TI" tel que décrit dans la littérature. L'objectif de notre travail est de proposer un cadre méthodologique permettant un meilleur pilotage des processus métiers, afin de tendre vers un alignement systématique de leur modélisation à leur implémentation au sein du système cible. En permettant la restitution intégrale d'un modèle transformé au sens de l'ingénierie inverse, notre plateforme permet une synchronisation entre modèle d’analyse et modèle d'implémentation.

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), Scholarly communication
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.854
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.019
Open science0.0000.000
Research integrity0.0000.000
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 head0.018
GPT teacher head0.241
Teacher spread0.224 · 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 designOther design
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
Published2012
Admission routes1
Has abstractyes

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