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Wayfinding in Complex Architectural Collections: A Collaborative Approach between Creator and Curator

2015· article· en· W4377837435 on OpenAlexaboutno aff
Maureen Jennings, Jennifer Garland, Sarah Severson, David Tkach

Bibliographic record

VenueArchiving Conference · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topic3D Surveying and Cultural Heritage
Canadian institutionsnot available
Fundersnot available
KeywordsArchivistDigitizationGlobeMetadataWorkflowArchitectureSpecial collectionsWorld Wide WebLibrary scienceWork (physics)Digital collectionsArt historySociologyComputer scienceVisual artsArtEngineeringDatabaseTelecommunications

Abstract

fetched live from OpenAlex

The Moshe Safdie Archive is the largest fonds administered by the John Bland Canadian Architecture Collection (CAC), Rare Books and Special Collections, McGill University, Montreal. In the 25 years since Safdie's original deposit to McGill University, advances in technology have changed the nature of architectural design and, consequently, how researchers access the collection [1], [2]. We were motivated to create a single, streamlined digitization workflow shared by both the Safdie Architects archivist and the CAC staff to economize time, labor, and resources. Additionally, through the use of embedded metadata developed with input from the architect himself, we sought to improve access to these materials as well as to facilitate effective research on the major themes in Moshe Safdie's work, which spans the globe and multiple decades.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.465

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.103
GPT teacher head0.260
Teacher spread0.157 · 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 designObservational
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
Published2015
Admission routes1
Has abstractyes

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