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Record W639067740

DEVELOPMENT OF THE FREQUENCY-MULTIPLIED, REFLECTED ELECTROMAGNETIC WAVE LANE MARKER SYSTEM

2000· article· en· W639067740 on OpenAlexaboutno aff
A. Nakatsuka, Satoshi Handa

Bibliographic record

VenuePROCEEDINGS OF THE 7TH WORLD CONGRESS ON INTELLIGENT SYSTEMS · 2000
Typearticle
Languageen
FieldEngineering
TopicEmbedded Systems and FPGA Design
Canadian institutionsnot available
Fundersnot available
KeywordsInterference (communication)USableDetectorEngineeringAcousticsComputer scienceObject detectionPosition (finance)Electrical engineeringPhysicsArtificial intelligencePattern recognition (psychology)
DOInot available

Abstract

fetched live from OpenAlex

This system operates by means of electro-magnetic wave in the lane marker system for detecting the lateral position of a vehicle in a highway lane. The previous system, which was a lane marker utilizing resonance reflective electro-magnetic wave and was introduced in last year's ITS World Conference 1999 in Toronto, possessed good detection performance but was susceptible to interference by nearby vehicles. Also, the applicable vehicle speed was 180km/h or slower. The new system described here solves the problem mentioned above with improved detection performance, and is considered fully usable in a real application due to its excellent detection performance, ease of installation of the lane markers and detectors, and the long service life. For the covering abstract see ITRD E114174.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.003

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 head0.016
GPT teacher head0.207
Teacher spread0.190 · 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 designBench or experimental
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

Citations0
Published2000
Admission routes1
Has abstractyes

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Same venuePROCEEDINGS OF THE 7TH WORLD CONGRESS ON INTELLIGENT SYSTEMSSame topicEmbedded Systems and FPGA DesignFrench-language works237,207