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Record W4389290533 · doi:10.14710/jpk.11.1.15-25

MODEL POTENSI PENDUDUK KOTA METROPOLITAN SEMARANG

2023· article· id· W4389290533 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

VenueJurnal Pengembangan Kota · 2023
Typearticle
Languageid
FieldSocial Sciences
TopicPublic Administration in Developing Nations
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsHumanitiesGeographyArt

Abstract

fetched live from OpenAlex

Saat ini di Kota Semarang belum tersedia informasi potensi penduduk yang mempertimbangkan interaksi spasial. Model Potensi penduduk adalah model spasial yang mencerminkan pemusatan penduduk berdasarkan interaksi antar wilayah. Penelitian ini bertujuan untuk mengkaji model dan persebaran potensi penduduk di Kota Semarang. Menggunakan metode deskripif kuantitatif serta pendekatan spasial dengan memanfatkan citra pengginderaan jauh dan Sistem Informasi Geografis. Potensi penduduk ditentukan berdasarkan model gravitasi yang mendasarkan pada jumlah penduduk dan jarak antara masing-masing kecamatan. Hasil penelitian menunjukkan bahwa potensi penduduk paling tinggi terdapat di Kecamatan Gayamsari sedangkan potensi penduduk paling rendah terdapat di Kecamatan Mijen. Kawasan yang mempunyai potensi penduduk rendah perlu didorong perkembangannya dengan penambahan fasilitas sehingga dapat meningkatkan mobilitas yang mencerminkan adanya aktivitas. Hasil penelitian dapat digunakan sebagai pertimbangan pemerintah dalam menentukan kebijakan terkait pemenuhan kebutuhan penduduk secara rasional yang mengarah pada pembangunan yang berkelanjutan.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.536
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.004

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 head0.076
GPT teacher head0.353
Teacher spread0.277 · 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