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Record W2533766694

Continuing the Narrative of Silo No. 5

2016· dissertation· en· W2533766694 on OpenAlexaboutno aff
Carmen Voda

Bibliographic record

VenueUWSpace (University of Waterloo) · 2016
Typedissertation
Languageen
FieldEngineering
TopicArchitecture, Modernity, and Design
Canadian institutionsnot available
Fundersnot available
KeywordsSiloNarrativeEngineeringHistoryVisual artsArchitectural engineeringArchaeologyArtLiterature
DOInot available

Abstract

fetched live from OpenAlex

Every modern city faces the challenge of how to engage the remains of its industrial past. Consciously or unconsciously, post-industrial cities have experienced a type of identity crisis after the decline of industries. Sites that once played a significant role in shaping their urban character are no longer economically productive. Some say these sites are akin to ancient ruins; however, the question of establishing an authentic connection between the contemporary city and its industrial past remains a cultural and architectural challenge. \n\tThe Lachine Canal in Montreal is a significant relic of Canadian industry. In the 19th century, industries were drawn to its edges to access water for both production and transportation of goods. Today, these obsolete machine-like structures lie dormant. Among them is Silo No. 5, which is located at the mouth of the Lachine Canal flow as it spills into the St. Lawrence River. Monumental in scale, the once productive structure has the magnitude of a great cathedral. \n\tAdmired by European modernist architects and historians, grain elevators like Silo No. 5 were identified as iconic structures of 20th Century architecture. This thesis seeks to re-invent and re-integrate Silo No. 5 into the contemporary city by reconciling its multiple identities. \n\tThe intent of this thesis is to understand not only the Lachine historic site, but also to celebrate the sublime atmosphere and the architectonic qualities of Silo No. 5. Two questions guide this exploration: “is it possible to re-introduce something obsolete back into the city?” and “how can we maintain the sublime power of the iconic industrial structure while at the same time allow it to become animated?”

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.109
Threshold uncertainty score0.216

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.019
Scholarly communication0.0070.004
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.183
Teacher spread0.176 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2016
Admission routes1
Has abstractyes

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