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Record W3209133088 · doi:10.22437/jop.v7i1.14632

APLIKASI METODE GEOLISTRIK RESISTIVITAS UNTUK MENGIDENTIFIKASI LAPISAN BAWAH PERMUKAAN JALAN RASAU JAYA, KABUPATEN KUBU RAYA

2021· article· id· W3209133088 on OpenAlex

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

VenueJOURNAL ONLINE OF PHYSICS · 2021
Typearticle
Languageid
FieldEngineering
TopicGeotechnical and construction materials studies
Canadian institutionsMedicine Hat College
Fundersnot available
KeywordsPhysicsGeomorphologyGeology

Abstract

fetched live from OpenAlex

Jalan Rasau Jaya Kabupaten Kubu Raya berpotensi mengalami kerusakan karena dibangun di atas lapisan yang diduga kurang kompak. Tujuan penelitian ini adalah untuk mengidentifikasi lapisan bawah permukaan di sekitar Jalan Rasau Jaya. Penelitian ini menggunakan metode geolistrik resistivitas dengan konfigurasi Wenner. Metode ini dapat mengidentifikasi sebaran nilai resistivitas bawah permukaan secara lateral. Nilai resitivitas yang diperoleh dijadikan acuan dalam mengidentifikasi lapisan bawah permukaan. Pengukuran dilakukan dengan mengaplikasikan 4 dengan panjang masing-masing 141 m, dan jarak antar elektroda sejauh 3 m. Hasil penelitian menunjukkan bahwa sebaran nilai resistivitas di lokasi penelitian sebesar 2 – 584 Ωm hingga kedalaman 23,6 m. Hasil interpretasi menunjukkan bahwa lapisan bawah permukaan terdiri dari 3 (tiga) lapisan. Lapisan pertama mempunyai nilai resistivitas 260 - 584 Ωm yang diinterpretasi sebagai pasir dan kerikil. Lapisan kedua mempunyai nilai resistivitas 11,1 – 259 Ωm yang diinterpretasi sebagai lapisan lempung berpasir. Lapisan ketiga mempunyai nilai resistivitas 2,0 – 10,1 Ωm, yang diinterpretasi sebagai lapisan akuifer.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.147
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.242
Teacher spread0.224 · 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