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Record W4255046555 · doi:10.32920/ryerson.14657544

A concept plan for Kennedy Mobility Hub: envisioning transit oriented development in Toronto's inner suburbs

2021· preprint· en· W4255046555 on OpenAlexaboutno aff
Kasper O. Koblauch

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicSmart Parking Systems Research
Canadian institutionsnot available
Fundersnot available
KeywordsTransit-oriented developmentPlan (archaeology)Transport engineeringPedestrianRetrofittingContext (archaeology)Transit (satellite)Urban planningLand useEnvironmental planningBusinessPublic transportDevelopment planArchitectural engineeringCivil engineeringEngineeringGeography

Abstract

fetched live from OpenAlex

This project presents a concept plan and vision for Kennedy Mobility Hub in Toronto, Ontario. The concept plan seeks to achieve six project goals, which are informed by a literature review, policy review, and context review. The goals are: to increase residential and employment density; achieve a more complete mix of transit-supportive land uses; replace all surface parking currently on developable public lands; improve the pedestrian and cyclist experience; expand greenspace; and ensure seamless transit mobility. The concept plan proposes extensive changes to the project area including mid-and high-rise development on all publicly owned surface parking lands. A number of new and extended roads are proposed to increase the area's permeability and facilitate development. Residential and employment densities for hypothetical development sites are calculated and discussed. The project highlights some of the pragmatic planning challenges, and potential solutions, associated with retrofitting commuter parking nodes to become transit-and pedestrian-oriented urban environments.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.202
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.282
Teacher spread0.257 · 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 teacher head, not a consensus.

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

Citations0
Published2021
Admission routes1
Has abstractyes

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