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Record W173181640

Best Practices in Sustainable Transportation

2010· article· en· W173181640 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueITE journal · 2010
Typearticle
Languageen
FieldEngineering
TopicSustainable Building Design and Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityOutreachCertificationBest practiceBusinessSustainable transportTransportation planningEnvironmental planningSustainable developmentNatural resourceTransport engineeringEngineeringEconomic growthEconomicsPolitical scienceManagementGeography
DOInot available

Abstract

fetched live from OpenAlex

The goal of sustainable transportation is to conserve natural resources and protect the environment while taking societal needs, benefits and costs into consideration. In this article, the authors argue that more information sharing, education and outreach is needed to create a best practices guide for sustainable transportation. This guide would include information on comprehensive land-use/transportation plans, design, construction, operations and maintenance. Such a guide would offer multiple options and ranges of solutions to suit local conditions. The experiences of cities such as San Francisco and Vancouver that have emerged as leaders in sustainability should be included in the best practices guide. The transportation industry can also look to the example of the building industry and its LEED certification system for inspiration in developing similar standards for transportation infrastructure.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.808
Threshold uncertainty score0.287

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.016
GPT teacher head0.285
Teacher spread0.270 · 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