MétaCan
Menu
Back to cohort
Record W2796368351 · doi:10.30997/jms.v3i2.891

Analisis Manfaat Biaya Program Orang Tua Asuh Pohon Mangrove Di Wilayah Pesisir Karawang

2017· article· id· W2796368351 on OpenAlexaff
Yudi Wahyudin, Helmi Purnama, Iman Teguh, Amal Fatullah Randy, Arif Trihandoyo, Agus Ramli, Muhammad Nur Arkham

Bibliographic record

VenueJurnal Mina Sains · 2017
Typearticle
Languageid
FieldEnvironmental Science
TopicMarine and Coastal Ecosystems
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsForestryMangroveBiologyGeographyEcology

Abstract

fetched live from OpenAlex

Tujuan dilakukan analisis manfaat biaya program orang tua asuh pohon mangrove ini adalah mengetahui manfaat dan kelayakan program OTAP (orang tua asuh pohon) mangrove bagi upaya pelestarian lingkungan hidup yang terintegrasi dan berkelanjutan. Metode penelitian dilakukan melalui penelusuran literatur dari dokumentasi aktivitas OTAP yang telah dilaksanakan Pertamina Hulu Energi Onshore North West Java (PHE ONWJ) dan metode penilaian kelayakan program yang digunakan adalah pendekatan analisis manfaat biaya yang diperluas. Analisis manfaat biaya program OTAP mangrove memberikan kelayakan ekonomi yang positif, sehingga bermanfaat bagi upaya pelestarian lingkungan hidup yang dilakukan di sekitar wilayah kerja PHE ONWJ. Nilai kelayakan dan keberlanjutan program OTAP mangrove yang dibuat dengan asumsi lama program (10 tahun) dan tingkat diskon (5%) menunjukkan nilai manfaat bersih sekarang yang positif sebesar Rp. 1,08 milyar, rasio manfaat biaya (2,06), dan tingkat pengembalian (19%). Kata Kunci: OTAP, ECBA, kelayakan program, jasa ekosistem, investasi hijau

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, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient 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 score0.335
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.265
Teacher spread0.249 · 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; both teacher heads agree on what is shown here.

Study designObservational
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

Citations4
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueJurnal Mina SainsSame topicMarine and Coastal EcosystemsFrench-language works237,207