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Record W4236731415 · doi:10.31227/osf.io/3c874

Tata Laksana Penerimaan Perkara

2018· preprint· id· W4236731415 on OpenAlexaff
Muhammad Rifqi Hidayat

Bibliographic record

Venuenot available
Typepreprint
Languageid
FieldSocial Sciences
TopicLegal Studies and Policies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Untuk memulai dan menyelesaikan pemeriksaan persengketaan perkara perdata yang terjadi di antara anggota masyarakat, salah satu pihak yang bersengketa, harus mengajukan permintaan pemeriksaan kepada pengadilan. Apabila salah satu pihak mengajukan permintaan pemeriksaan, persengketaan menjelma menjadi “perkara” di sidang pengadilan. Selama sengketa tidak meminta pengadilan untuk menanganinya maka pengadilan tidak berhak ikut campur dalam mengadili dan pengadilan tidak bisa berbuat apa-apa.Pengadilan berfungsi untuk memutuskan perkara-perkara yang diajukan kepadanya, dalam proses perkara tersebut terdapat prosedur yang harus dipenuhi oleh pihak pemohon atau penggugat sebagai pihak yang berperkara, dalam hal tersebut makalah ini akan memuat hal-hal yang terkait dengan prosedur pemohon atau penggugat dalam mengajukan perkara ke pengadilan agama khususnya.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.083
Threshold uncertainty score0.278

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0080.005
Open science0.0020.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0830.033

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 head0.050
GPT teacher head0.341
Teacher spread0.291 · 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 designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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