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Record W4324264904 · doi:10.25105/agora.v20i2.13835

OPTIMASI PEMANFAATAN JALUR PEJALAN KAKI DI KAWASAN NIAGA TERPADU SUDIRMAN

2023· article· id· W4324264904 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

VenueAGORA Jurnal Penelitian dan Karya Ilmiah Arsitektur Usakti · 2023
Typearticle
Languageid
FieldEngineering
TopicUrban Transport Systems Analysis
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Adanya integrasi antara fasilitas pejalan kaki dengan moda transportasi massal menjadi salahsatu daya tarik kawasan niaga terpadu Sudirman. Dengan fasilitas penunjang yang memadai,jalur pejalan kaki belum dapat mengakomodasi kegiatan dan kebutuhan pejalan kaki secaraoptimal. Penelitian ini bertujuan untuk mengetahui apakah pemanfaatan jalur pejalan kakiKawasan SCBD sudah optimal sehingga dapat memfasilitasi pejalan kaki besertakegiatannya. Pendekatan penelitian campuran dengan melakukan observasi lapangan dalammenilai tingkat keoptimalan fasilitas pejalan kaki, kemudian menyimpulkan data berdasarkanstandar dan tingkat pengaruh masing–masing aspek terhadap pejalan kaki dan menyajikandata secara kuantitatif. Temuan dari penelitian ini bahwa fasilitas pejalan kaki di KawasanSCBD belum optimal karena minimnya ruang atau fasilitas sosial dan kesenjangan jumlahpejalan kaki pada jam sibuk dan di luar jam sibuk. Hasil penelitian menyimpulkan bahwapemanfaatan jalur pejalan kaki dapat dioptimalkan melalui program penyediaan fasilitas danpelebaran jalur.Kata kunci : Jalur Pejalan Kaki, Kawasan Niaga Terpadu, Aktivitas Pejalan Kaki

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.206
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0030.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.009

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 head0.015
GPT teacher head0.225
Teacher spread0.211 · 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