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Record W3208518626 · doi:10.32920/ryerson.14649918.v1

Traversing the Lane Space

2021· preprint· en· W3208518626 on OpenAlexaboutno aff
Ashleigh Reagan Crofts

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicUrban Design and Spatial Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsRealmTraverseSpace (punctuation)PedestrianReinterpretationArchitecturePublic spaceComputer scienceArchitectural engineeringTransport engineeringEngineeringGeographyAestheticsPolitical scienceCartographyLaw

Abstract

fetched live from OpenAlex

Detouring between buildings subverts well-worn paths and reveals untapped space designated to Toronto’s extensive laneway network. Exploratory walks followed by creative transcription of the findings capture fragments that would otherwise go unnoticed. By harnessing new ways of reading the lane space, the proposed project envisions a lane-building-street hybrid, rich with urban retreats and alternate pedestrian paths. Through the reinterpretation of an existing laneway block as a catalyst, the scheme explores strategies that grant this hybrid space to curious strollers, challenging highly-regulated and standardized street space as the primary means of moving through the contemporary city. These strategies invigorate the role of architecture in enhancing the quality of urban life, rewarding pedestrians with access to the city through new routes, expanded public realm, and countless discoveries.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.923
Threshold uncertainty score0.960

Codex and Gemma teacher scores by category

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

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 head0.011
GPT teacher head0.176
Teacher spread0.165 · 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 designSimulation or modeling
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
Published2021
Admission routes1
Has abstractyes

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