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Record W4408151784 · doi:10.22487/jpwkt.v1i1.3

Perubahan Penggunaan Lahan Di Kecamatan Parigi Kabupaten Parigi Moutong

2022· article· id· W4408151784 on OpenAlexaff
Muhammad Syafaat Danish Muhammad Syafaat Danish, Abdul Gani Akhmad Abdul Gani Akhmad, Rusli Rusli, Rizkhi Rizkhi

Bibliographic record

VenueJurnal PeWeKa Tadulako · 2022
Typearticle
Languageid
FieldAgricultural and Biological Sciences
TopicPlant Growth and Agriculture Techniques
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Kecamatan Parigi terus mengalami perubahan penggunaan lahan yang pesat, mulai dari pembangunan kawasan perkantoran, permukiman, perdagangang dan jasa serta sarana prasarana, seiring berjalannya waktu perubahan lahan terus mengalami perkembangan dari lahan lahan kosong berubah menjadi lahan terbangun dan lahan pertanian berubah menjadi non pertanian serta lahan pertanian berubah menjadi permukiman. Penelitian ini memiliki tujuan Menganalisis perubahan penggunaan lahan dan jenis perubahan penggunaan lahan di Kecamatan Parigi dalam kurun waktu 10 tahun terakhir dan menganalisis pola sebaran penggunaan lahan di Kecamatan Parigi dalam kurun waktu 10 tahun terakhir di Kecamatan Parigi dengan metode deskriptif kualitatif, analisis overlay dan analisis nearest neighbor dari hasil analisis yang di gunakan hal yang ingin di capai iyalah melihat perubahan penggunaan lahan yang terjadi pada tahun 2010 hingga 2021, serta pola sebaran permukiman.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.479
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.015
GPT teacher head0.207
Teacher spread0.193 · 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 designNot applicable
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
Published2022
Admission routes1
Has abstractyes

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