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Record W6987020402

Roundabouts and other intersections. [Formerly known as: Roundabouts.]

2021· other· en· W6987020402 on OpenAlexaboutno aff

Bibliographic record

VenueData Archiving and Networked Services (DANS) · 2021
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsRoundaboutSAFERIntersection (aeronautics)Traffic calmingScope (computer science)Road trafficPedestrianQuarter (Canadian coin)Geometric design
DOInot available

Abstract

fetched live from OpenAlex

An intersection is a location where roads intersect or split and where road users may change direction. There are two main groups of intersections: unprioritised intersections and prioritised intersections. At the former intersection, drivers coming from the right have right of way. Intersections may have three, four, or five legs, and they may have been designed differently. At priority intersections, right of way is controlled by traffic signs, road markings and/or traffic lights. About one third of the road deaths on Dutch roads occur at intersections. Within the urban area, this amounts to half and outside the urban area to slightly less than a quarter of the road deaths. Among cyclists and (light) moped riders relatively many road deaths occur at intersections. A roundabout is the safest kind of intersection, because there are fewer conflict zones, because speed is lower, and impact angles are smaller than at a conventional intersection. For cyclists and pedestrians, roundabouts are also safer than other kinds of intersections; at least in the Netherlands they are. Sustainable Safety advises roundabouts at locations where two distributor roads intersect. In general, Sustainable Safety only allows conflicts between vehicles when they do not differ greatly in speed and/or mass. That is why, from a road safety perspective, speed reduction measures are needed at or near intersections. Apart from the intersections, there are also multi-level and level crossings, but these fall outside the scope of this fact sheet. At multi-level crossings, no traffic is exchanged and therefore the conflicts that occur at other intersections are avoided. At level crossings, facilities for other kinds of traffic are crossed, for example public transport facilities (see SWOV fact sheet Public transport and level crossings at https://www.swov.nl/en/facts-figures/factsheet/public-transport-and-level-crossings) or pedestrian and bicycle crossings (see SWOV fact sheet Infrastructure for pedestrians and cyclists at https://www.swov.nl/en/facts-figures/factsheet/infrastructure-pedestrians-and-cyclists).

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)0.001
metaresearch head score (Gemma)0.003
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 score0.098
Threshold uncertainty score0.328

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.005
Science and technology studies0.0020.001
Scholarly communication0.0030.005
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0980.035

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 head0.023
GPT teacher head0.282
Teacher spread0.259 · 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
Published2021
Admission routes1
Has abstractyes

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