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Record W7019200601

Fast Forward 2018: Jodi and Andrew Batay-Csorba (Toronto)

2018· other· en· W7019200601 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Auckland Data Repository · 2018
Typeother
Languageen
FieldEngineering
TopicArchitecture, Modernity, and Design
Canadian institutionsnot available
Fundersnot available
KeywordsArchitectureWork (physics)Unitary stateSession (web analytics)Placemaking
DOInot available

Abstract

fetched live from OpenAlex

Take a look at the work of this young Canadian firm and you will discover how well medium density is doing in Toronto. Founded in 2010, Batay-Csorba Architects have received many awards and are widely published. Their work ranges across installation, interior design, architecture and urban design. Through careful design of sites and delight with materiality, they create great interior spaces and make positive contributions to the urban environment. Their three to four storey duplex houses are excellent examples of that typology. This session presents timely insights as we come to grips with possibilities unleashed by Auckland's new inner city zones in the Unitary Plan. Jodi and Andrew's visit to New Zealand has been organised in collaboration with the New Zealand Institute of Architects.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.450
Threshold uncertainty score0.894

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0050.001
Scholarly communication0.0080.004
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.4060.190

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 head0.012
GPT teacher head0.186
Teacher spread0.174 · 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.

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
Published2018
Admission routes1
Has abstractyes

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