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Record W4404904810 · doi:10.53893/pilar.v19i2.9485

PERANCANGAN JEMBATAN I GIRDER DAN TRUSS SISTEM KOMPOSIT BENTANG 110 METER LAHAT SUMATERA SELATAN

2024· article· en· W4404904810 on OpenAlexaff
Nurcahaya, Sara Shapiyah, Raja Marpaung, Lina Flaviana Tilik

Bibliographic record

VenuePILAR · 2024
Typearticle
Languageen
FieldEngineering
TopicGeotechnical and construction materials studies
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsTrussGirderBridge (graph theory)Structural engineeringEngineeringBiology

Abstract

fetched live from OpenAlex

A bridge is a construction that connects two or more separate areas. Bridges owned by PT. Bara Alam Utama is located in Banjarsari, Lahat Regency, South Sumatra. This bridge is used as an alternative way to bring mining products in the form of coal to the storage station. The total length of the bridge is 110 meters. This bridge is divided into 3 segments, namely the first segment is the beam I bridge, the second segment is the steel frame bridge and the third segment is the beam I bridge. The beam I bridge has a length of 25 m and the steel frame bridge has a length of 60 m. This bridge system uses a composite system of a combination of concrete and steel frames. The planning includes the superstructure and the substructure. From the results of the sondir test, the abutments and pillars are not able to withstand the sliding bearing capacity, therefore piles with a spunpile type with a diameter of 80 cm are used. Bridge planning is guided by RSNI T-12-2004, RSNI T-03-2005, SNI 2833-2016, SNI 1725-2016 and other library sources.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0220.005

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 head0.005
GPT teacher head0.183
Teacher spread0.178 · 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 designSimulation or modeling
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
Published2024
Admission routes1
Has abstractyes

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