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Record W4401090966 · doi:10.58860/jti.v3i7.441

Analisis Kinerja dan Tingkat Pelayanan Ruas Jalan Raya Ciomas Kreteg Kabupaten Bogor

2024· article· en· W4401090966 on OpenAlex
Vigie Priantika Putra Hutama

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

VenueJurnal Teknik Indonesia · 2024
Typearticle
Languageen
FieldEngineering
TopicUrban Transport Systems Analysis
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsTransport engineeringTraffic flow (computer networking)Data collectionPopulationMathematicsStatisticsOperations managementGeographyBusinessEngineeringComputer scienceComputer network

Abstract

fetched live from OpenAlex

The development of transportation has an impact on increasing traffic flow. The increase in the number of vehicles and high levels of human movement will cause congestion if it is not balanced with adequate road infrastructure. The aim of the research is to identify the level of service and performance of road sections. Methodology is a method or technique used to test the validity of using certain research. The research location is on Jalan Raya Ciomas Kreteg, Bogor Regency because it is a residential and commercial area so it is busy every day. Data collection techniques are taken through surveys of geometric conditions, traffic flow, speed and side obstacles. The supporting data is obtained from the population according to the Central Statistics Agency. The survey was carried out during rush hour and it was discovered that the traffic volume was 1216.75 pcu / hour. The analysis results show that the capacity of Jalan Raya Ciomas Kreteg is 2201.45 pcu / hour and DS is 0.55, so the Jalan Raya Ciomas Kreteg section is in class C in the classification of road service levels.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.206
Teacher spread0.198 · 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