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Record W2616730879 · doi:10.4000/cybergeo.28067

Métabolisme urbain et quartiers péricentraux dans la métropolisation. L’exemple du quartier de Saint-Michel à Montréal

2017· article· fr· W2616730879 on OpenAlexaboutno aff
Violaine Jolivet, Marie‐Noëlle Carré

Bibliographic record

VenueCybergeo · 2017
Typearticle
Languagefr
FieldEnvironmental Science
TopicSustainability and Ecological Systems Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtPolitical science

Abstract

fetched live from OpenAlex

Les débats sur la promotion territoriale à l’échelle internationale mettent toujours plus largement en avant la qualité de vie et la durabilité urbaine comme des avantages concurrentiels. Or, peu de travaux ont exploré les interactions entre l’insertion des villes dans la mondialisation et le métabolisme urbain à l’échelle locale. À partir d’une approche en études urbaines et en écologie politique, cet article s’appuie sur le cas de Montréal (Québec, Canada), et explore les mutations du quartier péricentral de Saint-Michel sur plus d’un demi-siècle. Il interroge la métropolisation dans sa dimension spatio-temporelle à la lumière des relations entre économie, politique et environnement dans un espace marqué par l’activité extractive (carrières) et accumulative (déchets).

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)0.000
metaresearch head score (Gemma)0.000
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 score0.160
Threshold uncertainty score0.323

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.000

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 head0.008
GPT teacher head0.242
Teacher spread0.234 · 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

Citations7
Published2017
Admission routes1
Has abstractyes

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