MétaCan
Menu
Back to cohort
Record W1524007543 · doi:10.4000/cybergeo.7872

Analyse des aires de marché du commerce de détail à Québec : une méthodologie combinant une enquête de mobilité et un système d’information géographique

2011· article· fr· W1524007543 on OpenAlexaffabout
Gjin Biba, Marius Thériault, François Des Rosiers

Bibliographic record

VenueCybergeo · 2011
Typearticle
Languagefr
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHumanitiesMetropolitan areaPolitical scienceGeographyArt

Abstract

fetched live from OpenAlex

Cet article présente une méthodologie utilisée pour étudier la compétition entre les rues commerciales, les centres d’achat et les magasins entrepôts dans la région métropolitaine de Québec en 2001. Basée sur la synthèse des comportements de mobilité individuels visant des fins de consommation issus d’une vaste enquête origine–destination, la procédure d’analyse utilise les SIG pour modéliser les déplacements réalisés sur le réseau routier afin de prendre en compte les perturbations d’accessibilité liées aux infrastructures de transport. Elle permet de délimiter des aires de marché primaire et secondaire pour chaque agglomération commerciale, d’étudier leur degré de compétition spatiale et d’élaborer un diagnostic préliminaire sur l’effet global de l’implantation récente de plusieurs magasins entrepôts en relation avec la viabilité des centres commerciaux et des rues commerciales traditionnelles.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.194
Threshold uncertainty score0.391

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.006
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.054
GPT teacher head0.299
Teacher spread0.245 · 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 designObservational
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

Citations4
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueCybergeoSame topicUrban Transport and AccessibilityFrench-language works237,207