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Record W7128867406

Les spécificités des espaces publics à l'échelle du territoire de Montréal. Cahier In.SITU 9

2023· other· en· W7128867406 on OpenAlexaboutno aff
Guillaume Éthier, François Racine

Bibliographic record

VenueArchipelago (Université du Québec à Montréal) · 2023
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsPublicsNational libraryTransformation (genetics)
DOInot available

Abstract

fetched live from OpenAlex

Le projet Espaces Publics (P.E.P) est une recherche réalisée en 3 volets par une équipe pluridisciplinaire de la Chaire internationale sur les usages et pratiques de la ville intelligente (ESG UQAM) pour le compte de la Ville de Montréal. En lien avec l’élaboration du Plan d’urbanisme et de mobilité (PUM) et du Projet de ville (2021) définissant les partis pris municipaux, les grands défis à relever et les éléments de vision pour guider la transformation de la ville d'ici 2050, la recherche contribue à « Définir une stratégie d’intervention pour la transformation des espaces publics de Montréal ». La recherche est constituée de trois volets. Ce rapport expose les résultats du volet 1. Il a pour but de définir et cerner les différents types d’espaces publics présents sur le territoire de Montréal en incluant la composante morphologique et celles des usages.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.072
Threshold uncertainty score0.242

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0050.002
Scholarly communication0.0050.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0720.004

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 head0.194
Teacher spread0.182 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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