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Record W7055167168

Canada, le citta sotterranee

2011· article· en· W7055167168 on OpenAlexaboutno aff

Bibliographic record

VenueAirIuav (Università Iuav di Venezia) · 2011
Typearticle
Languageen
FieldEngineering
TopicLaser Design and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsArchipelagoPedestrianResource (disambiguation)PopulationSquare (algebra)
DOInot available

Abstract

fetched live from OpenAlex

Canada is an immense archipelago of islands and satellite cities, with several highly urbanized regions around the great metropolises of Montréal, Toronto, Vancouver and Ottawa, where half of the population is concentrated. For the great metropolises with extreme climates, the underground could be an important resource that could modify the overall fruition of the urban structure, with an interesting impact on the organization of the territory and landscape.\nOne of the major cities built underground at the international level is the Ville\nSouterraine or RESO in Montréal, 32 km of pedestrian paths and shopping malls,\n12 square metres of multipurpose spaces perfectly integrated into 41 districts\nabove ground. Built in the 1960s and later expanded, this complex, which has 120 entrances, is used by 500,000 people every day.\nToronto, divided into two parallel cities, one on the surface and one underground, is internationally recognized for the PATH, one of the most extensive shopping complexes that is perfectly integrated with a pedestrian circulation system with facilities and vertical connections. The PATH plays an important role not only in the economic growth and urban evolution of Toronto, but is also an alternative way of experiencing the heart of the city. The Masterplan which was developed offers a targeted approach to growth and to the\ndevelopment of the underground city.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.309
Threshold uncertainty score0.883

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 head0.019
GPT teacher head0.160
Teacher spread0.141 · 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 designNot applicable
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
Published2011
Admission routes1
Has abstractyes

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