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Record W7039730004

30/30 Museum & Park: Engaging Artifacts

2017· article· en· W7039730004 on OpenAlexaboutno aff

Bibliographic record

VenueUA Campus Repository (The University of Arizona) · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicEducation, Innovation and Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFactory (object-oriented programming)Natural (archaeology)Vegetation (pathology)Cultural artifactAtmosphere (unit)Host (biology)
DOInot available

Abstract

fetched live from OpenAlex

This project is located in the St. Henri neighborhood along the Lachine Canal in Montreal, Quebec. Industrial artifacts along the canal are culturally and historically significant to the people of Montreal. These artifacts are currently disconnected from public access – residents and tourists should be able to fully engage with them. The abandoned malting plant site has the potential to become an engaging destination that visitors want to explore. The proposal honors and reimagines the site’s industrial infrastructure and introduces valuable public amenities to the Lachine Canal. The 30/30 concept refers to the juxtaposition of the existing thirty silos and proposed thirty mounds. Generated from the volumetric capacity of the silos and natural form of grain, the mounds support vegetation to restore the sites pre-industrial presence of nature. Museum functions and public spaces are integrated into both the silos and mounds, resulting in an activity-driven experience for visitors that is centered on exploration and discovery. The proposal has the potential to host events, exhibitions, and outdoor activities year-round. By allowing guests to "trespass" through urban artifacts, they are invited to discover the mysterious atmosphere and cultural significance of the former factory and the site’s new public amenities.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.686
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0060.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.290
Teacher spread0.262 · 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.

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
Published2017
Admission routes1
Has abstractyes

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