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Record W7042942096

3rd ISUFitaly International Congress I Rome, 23-24 February 2017 - BOOK OF ABSTRACTS

2017· article· en· W7042942096 on OpenAlexaboutno aff

Bibliographic record

VenueIRIS Research product catalog (Sapienza University of Rome) · 2017
Typearticle
Languageen
FieldEngineering
TopicUrban Design and Spatial Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsGeorge (robot)PhenomenonUrban designUrban planningProcess (computing)ArchitectureWork (physics)State (computer science)Urban structure
DOInot available

Abstract

fetched live from OpenAlex

When George Baird, architect and researchist in urban morphology, studied Toronto’s urban fabric in \n1978, he examined the morphological transformations of its central core and showed that the urban \nfabric in some parts of this North American city was in the process of desintegration (Baird 1978). This \nphenomenon also affected the urban fabric of Montreal, and the urban design projects, related to \na modernistic approach, built in the 1960s, were responsible for these transformations and provoked \na spatial discontinuity (Charney et al. 1990). The paper will study projects from the modernist period, \nbut will also include the postmodernist and the contemporary periods to determine the new urban \ndesign approach and to evaluate the relationship of these projects with the urban fabric of Montreal. We have endeavoured to study three major urban design projects in Montreal from 1950 to 2014 \nto determine their role in the progression of the phenomenon of desintegration. With the work of numerous urban morphologists on North American cities (Charney, Vernez-Moudon, Gauthier, Racine) \nand the impact of this more recent knowledge on the way we intervene on the fabric, this phenomenon should be in regression in Montreal as elsewhere. Our hypothesis is that the reinterpretation \nof the urban syntax in the process of designing urban fabric in Montreal is a solution to reestablish a \ndialog between new built environments and the historical fabric of the city. But is this new research \nfor continuity still in a fragile state ?

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.502
Threshold uncertainty score0.716

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0030.001
Scholarly communication0.0070.002
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.4980.290

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 head0.046
GPT teacher head0.288
Teacher spread0.241 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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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