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Record W3049693416

Contributions au problème d'affectation des types d'avion

2004· article· fr· W3049693416 on OpenAlexaboutno aff
Nicolas Bélanger

Bibliographic record

VenuePolyPublie (École Polytechnique de Montréal) · 2004
Typearticle
Languagefr
FieldEngineering
TopicScheduling and Optimization Algorithms
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Processus de planification en transport aérien -- Potentiel de bénéfices lié à l'optimisation de la planification -- Définition du problème -- Formalisation du problème de planification -- Affectation des types d'avion aux vols averc horaire flexible -- Affectation hebdomadaire des types d'avion aux vols ave homogénéité -- Weekly airline fleet assigment with homogeneity -- Modèle raffiné pour l'homogénéité -- Autres approches heuristiques -- Résultats numériques détaillés -- Application chez Air Canada -- Extensions -- Etude de cas chez Air Canada -- Affectation des types d'avion aux vols avec flexibilité d'horaire -- Periodic airline fleet assignment with time windows, spacing constraints, and time dependent revenues -- Difficultés au niveau de la résolution en nombres entiers -- Résultats numérique détaillés.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.030
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.009
GPT teacher head0.229
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations1
Published2004
Admission routes1
Has abstractyes

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