MétaCan
Menu
Back to cohort

Comparing Safety Performance Measures Obtained from Video Capture Data

2011· article· en· W1982721991 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

VenueJournal of Transportation Engineering · 2011
Typearticle
Languageen
FieldEngineering
TopicTraffic and Road Safety
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsRoundaboutCollisionCrashComputer scienceMeasure (data warehouse)Transport engineeringSituatedSimulationEngineeringData miningComputer securityArtificial intelligence

Abstract

fetched live from OpenAlex

Safety performance is evaluated by using measures obtained experimentally from a videotaping of traffic operations at an urban roundabout situated in Cosenza, Italy. Five different expressions of safety performance from the perspective of “rear-end” vehicle interactions include maximum deceleration rate to avoid a crash (DRAC), time-to-collision (TTC), proportion of stopping distance (PSD), time integrated time-to-collision (TIT), and crash potential index (CPI). Differences in safety performance are discussed with respect to the type of measure, traffic conditions, and variations in roundabout geometry. The results of this analysis suggest that safety performance is highly sensitive to the way it is measured; different measures can highlight different locations or geometric features of the roundabout as posing potential safety problems. This study underscores the usefulness of safety performance measures for providing meaningful experimental indicators of potential safety problems at roundabouts and how these problems can be affected by changing traffic conditions.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.719
Threshold uncertainty score0.635

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 integrity0.0000.000
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 head0.033
GPT teacher head0.195
Teacher spread0.161 · 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