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Record W2012648166 · doi:10.13031/2013.18179

Nighttime Impaired Driving in Rural Alberta

2005· article· en· W2012648166 on OpenAlexaboutno aff
Kathy Belton, Gian S. Jhangri, S. D. MacDonald, Donald C. Voaklander

Bibliographic record

VenueJournal of Agricultural Safety and Health · 2005
Typearticle
Languageen
FieldEngineering
TopicVehicle emissions and performance
Canadian institutionsnot available
Fundersnot available
KeywordsDemographicsPoison controlInjury preventionEnvironmental healthHuman factors and ergonomicsOccupational safety and healthSuicide preventionRural areaGeographySpeed limitTransport engineeringSocioeconomicsMedicineDemographyEngineering

Abstract

fetched live from OpenAlex

A nighttime roadside survey of rural Alberta drivers was conducted to quantify the nature and extent of impaired driving on Alberta's rural roads during nighttime. The survey also sought to describe driver demographics and information about the trip, such as origin and destination, among rural Alberta's nighttime drivers. Surveys were administered to drivers of vehicles that were randomly sampled at rural locations in Alberta between the hours of 10:00 PM and 4:00 AM between 22 August and 1 September 2001. Drivers who agreed to participate were asked a series of short questions. The interview concluded with the driver providing a breath sample to measure the driver's BAC level. Of the drivers surveyed, 3% had a BAC that was over the legal limit of 80 mg%. A total of 13% of drivers tested had detectable amounts of alcohol in their system.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.855
Threshold uncertainty score0.202

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)0.0000.000

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 head0.007
GPT teacher head0.229
Teacher spread0.221 · 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 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

Citations6
Published2005
Admission routes1
Has abstractyes

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