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Record W2752977365 · doi:10.24904/footbridge2017.09790

Fort York Pedestrian Bridges in Toronto. The Two First Duplex Stainless Steel Bridges in North America

2017· article· en· W2752977365 on OpenAlexaboutno aff
Juan A. Sobrino, Javier Jordán, Sergio Carratalá, Diego Sisi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPedestrianArchBridge (graph theory)EngineeringPedestrian crossingTransport engineeringTelecommunicationsArchitectural engineeringCivil engineering

Abstract

fetched live from OpenAlex

<p>In April 2015, the city of Toronto selected a proposal for the Fort York Pedestrian and Cycle Bridge project in a design-build competition. The project provides a key link between Stanley Park to the north and the historic area of Fort York – the birth place of Toronto- crossing two rail corridors. Construction started in August 2016 and completion is expected by the end of 2017.</p> <p>The connection includes two pedestrian bridges. The awarded design proposal includes an unprecedented technical innovation in North America: the use of Duplex Stainless Steel on the entire structure. This pioneering use of a forefront technology provides premium aesthetics within a unique setting in addition to a safe and durable asset for the community. The structure has an extended life cycle, is more corrosionresistant and requires less maintenance, reducing its overall cost.</p> <p>Each bridge is supported by a single arch rib inclining at 18° to provide a slender, transparent and elegant impression. The two arches tilt in opposite direction, and the overall layout resembles a Yin & Yang shape to emphasize both contrast and continuity, expressing a modern, understated and elegant aesthetic.</p>

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.491
Threshold uncertainty score0.970

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 head0.015
GPT teacher head0.249
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 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
Published2017
Admission routes1
Has abstractyes

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