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Record W7099588040

Montana Code Annotated and Administrative Rules of Montana Basis for a Speed Law Violation: Basic Speed Rule:

2013· article· en· W7099588040 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTraffic and Road Safety
Canadian institutionsnot available
Fundersnot available
KeywordsSpeed limitStatutory lawPopulationPoint (geometry)State (computer science)Limit (mathematics)LegislationWork (physics)
DOInot available

Abstract

fetched live from OpenAlex

Subject to the (maximum) statutory speed limits below, a person shall operate a vehicle in a careful and prudent manner and at a reduced rate of speed no greater than is reasonable and prudent under the conditions existing at the point of operation, taking into account the amount and character of traffic, visibility, weather and roadway conditions. 1 '61-8-303(4) 75 MPH 2 at all times on Federal-Aid interstate highways outside an urbanized area with population ≥50,000 '61-8-303(1)(a) 65 MPH 2 at all times on Federal-Aid interstate highways within an urbanized area with a population ≥50,000 '61-8-303(1)(a) 70 MPH 2 during the daytime 3 and 65 MPH 2 during the nighttime 3 on any other public highway '61-8-303(1)(b) 65 MPH at all times on U.S. Highway 93 between the Canadian and Idaho boarders unless the highway is upgraded to a continuous four lane highway. '61-8-303(2) 25 MPH in an urban district '61-8-303(5) I. The State Department of Transportation, based on engineering and traffic investigations which indicate that a greater or less speed limit than noted above is reasonable or safe, may establish different speed limits on a segment of a highway less than 50 miles in length. '61-8-309(1) The law does not specifically state whether different highway speed limits may be established either for different types of vehicles, for various weather conditions or for different times of the day.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.337
Threshold uncertainty score0.670

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0080.001
Scholarly communication0.0070.002
Open science0.0030.002
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.1010.055

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 head0.020
GPT teacher head0.239
Teacher spread0.218 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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
Published2013
Admission routes1
Has abstractyes

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