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Record W7024295808

A Road that divided a city: Assessing the key factors that influences the decision to rebuild the Gardiner Expressway East in Toronto

2016· other· en· W7024295808 on OpenAlexaboutno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2016
Typeother
Languageen
FieldEngineering
TopicUnderground infrastructure and sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsKey (lock)Government (linguistics)Context (archaeology)Work (physics)Identification (biology)
DOInot available

Abstract

fetched live from OpenAlex

Alors que la planification du transport s’était longtemps attardée sur la voiture, les urbanistes d’aujourd’hui repensent la priorité donnée à l’automobile dans les réseaux de transports urbains. Les autoroutes urbaines construites dans les années 50 et 60 nécessitent des réparations majeures, ce qui donne la chance aux villes de changer leur façon de faire en ce qui a trait au transport et développement urbain pour devenir plus efficace et durable.[...] Alors que la théorie en urbanisme s’est éloignée de la planification des transports centrée sur l’automobile, la décision de la Gardiner Expressway démontre qu’une grande partie de la société n’est pas de cet avis; l’inquiétude suscitée par le potentiel du changement en infrastructure d’augmenter les temps de déplacement et la congestion de la circulation, même légèrement, ne peut être sous-estimée. Plus généralement, ce résultat démontre l'importance de la politique dans les questions d’aménagement et remet en question la valeur accordée à l'expertise professionnelle des urbanistes dans les décisions de planification des transports.

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)0.003
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 score0.135
Threshold uncertainty score0.271

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.002
Scholarly communication0.0030.001
Open science0.0010.002
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 head0.019
GPT teacher head0.258
Teacher spread0.239 · 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
Published2016
Admission routes1
Has abstractno

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