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Record W2348672795

Autopsy: Redesigning Urban Transportation

2010· dissertation· en· W2348672795 on OpenAlexaboutno aff
Gregory McKay Perkins

Bibliographic record

VenueUWSpace (University of Waterloo) · 2010
Typedissertation
Languageen
FieldMedicine
TopicAutopsy Techniques and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsEngineeringTransport engineeringMedicine
DOInot available

Abstract

fetched live from OpenAlex

According to the United Nations’ report, State of World Population 2008, humankind has come to a turning point; more than 50% of the earth’s population now lives in urban centres. Along with considerations for housing, employment, and public health, this shift changes the way we design roads and streets; it escalates the number of automobiles in urban areas with finite room for road expansion. 
\n\tSpace constraints, along with intense development of alternative transportation fuels, and the burden of sprawling suburbs on municipal infrastructures suggest the hypothesis that before we run out of energy alternatives for personal mechanized transport, we will run out of space in which to use it.
\n\tThis thesis explores how Toronto, a city largely designed for automobile use, is being re-adapted into a city wherein public and active transportation can once again be the primary means of urban mobility and the opportunities inherent in the development of interregional multi-modal transit stations for the cultivation of civic space, local commerce, urban form, and commercial transportation.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.816
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.010
GPT teacher head0.226
Teacher spread0.216 · 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 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
Published2010
Admission routes1
Has abstractyes

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