MétaCan
Menu
Back to cohort
Record W4251218245 · doi:10.32920/ryerson.14655102.v1

Inhabitable Bridge Infrastructure: A Reappropriation of the Street from Vehicular to Pedestrian Scale

2021· preprint· en· W4251218245 on OpenAlexaboutno aff
Sacha Marthinez

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsBridge (graph theory)PedestrianTransport engineeringVitalityScale (ratio)EngineeringArchitectural engineeringCivil engineeringGeographyCartography

Abstract

fetched live from OpenAlex

For the past century urban infrastructures have been designed primarily with automobile use in mind. The built environment consequently reflects a neglect of the human scale, that is, pedestrians. This thesis looks at existing contemporary bridges and explores ways of bringing pedestrian-scaled activity and vitality back onto the bridge, thereby breaking the confines of vehicular bridges to create a continuum of the urban environment on both ends. This thesis investigates methods of integration and coordination of vehicular and pedestrian traffic as a way to maintain the bridge as a “connector” for transport purposes, resulting in a future where bridges may facilitate a higher quality urban environment. The site for this thesis is the Jacques Cartier Bridge, a vehicular bridge that spans the St. Lawrence River in Montreal. This thesis examines the history of the street versus the road, place versus non-place, mobility versus transport and the influence of the Megastructuralist movement in Montreal as applicable elements for future bridge design. This thesis will also find ways to reacquaint itself with the estranged concept of the inhabitable bridge and demonstrating how it can be reintegrated into current and future infrastructural bridge concepts.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.449
Threshold uncertainty score0.795

Codex and Gemma teacher scores by category

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

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 head0.007
GPT teacher head0.199
Teacher spread0.192 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Explore more

Same topicStructural Engineering and Vibration AnalysisFrench-language works237,207