MétaCan
Menu
Back to cohort
Record W2016558995 · doi:10.1177/1087724x0044001

Using Technology in Surface Transportation to Save Lives, Time, and Money

2000· article· en· W2016558995 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePublic Works Management & Policy · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicTransportation Planning and Optimization
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsGridlockSoftware deploymentTraffic congestionBureaucracyLegislationBusinessPublic transportTransport engineeringIntelligent transportation systemEngineeringPolitical sciencePolitics

Abstract

fetched live from OpenAlex

Despite aggressive highway construction and efforts to promote nonhighway modes of travel, the United States has seen traffic congestion grow to unprecedented levels that threaten to gridlock both commuting and commerce. But many municipalities are now using intelligent transportation systems (ITS) to reduce congestion and improve the efficiency of existing transportation networks. Recent legislation has spurred research in and deployment of ITS, but it is the private market that will build on these investments over the next 20 years. ITS America is at the forefront of the revolution, coordinating public and private efforts in ITS and developing programs to educate and train the new generation of ITS-savvy transportation professionals. In addition, ITS America is both educating the public about the benefits of adopting ITS and working to overcome the bureaucratic, technical, and institutional hurdles to the widespread adoption of these systems.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.476
Threshold uncertainty score0.434

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.017
GPT teacher head0.300
Teacher spread0.283 · 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