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Record W2621084182

Perencanaan Geometrik Simpang Susun Double Trumpet Pada Jalan Tol Jakarta – Serpong Berdasarkan Transportation Association Of Canada Geometric Design Guide 2007

2017· article· id· W2621084182 on OpenAlexaboutno aff
Hadiranti Hadiranti, Sofyan Triana

Bibliographic record

VenueREKA RACANA · 2017
Typearticle
Languageid
FieldEngineering
TopicGeotechnical and construction materials studies
Canadian institutionsnot available
Fundersnot available
KeywordsGeometric designMathematicsPhysicsGeometryEngineering
DOInot available

Abstract

fetched live from OpenAlex

ABSTRAK PT. Bintaro Serpong Damai telah merencanakan Jalan Tol Jakarta-Serpong sejak Tahun 1993 dan belum direalisasikan pembangunannya. Perancangan ulang dilakukan menggunakan peraturan TAC  (Transportation Association of Canada) Geometric Design Guide 2007. Perancangan alinyemen horisontal dan alinyemen vertikal   dengan superelevasi maksimum 6% dan kecepatan rencana 40 km/jam. Perancangan lengkung horisontal dibuat dua buah lengkung compound curve menggunakan gabungan radius yaitu R1= 200 m dan R2= 75 m. Panjang lengkung On Ramp 01 berdasarkan TAC 2007 L= 395,6 m dan lengkung vertikal cembung L= 8 m menggunakan faktor k= 4 dan A= 2 %. Kata kunci : Alinyemen, Simpang Susun, Compound Curve. ABSTRACT T. Bintaro Serpong Damai had planned Jakarta-Serpong Toll Road since 1993 and the development has not been realized. This research redesign using TAC (Transportation Association of Canada) Geometric Design Guide 2007. The horizontal alignment and vertical alignment design using maximum superelevation 0.06 and speed plans 40 km / h. The horizontal curved design consist of two curved compound curve and using the combined radius is R1 = 200 m and R2 = 75 m. On Ramp 01 arch length by TAC Geometric Design Guide 2007 is L = 395,6 m and a vertical crest curved design using factor k = 4, and A = 2% is L = 8 m. Keywords : Alignment, Interchange, Compound Curve.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.476
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.219
Teacher spread0.205 · 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.

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

Citations0
Published2017
Admission routes1
Has abstractyes

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