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Record W4411607802 · doi:10.22487/peweka.v3i2.38

Penilaian Geosite Palukoro Di Lembah Palu

2024· article· id· W4411607802 on OpenAlexaff
Nur Miftahul Jannah, Rizkhi, Amar, Iwan Setiawan Basri, Vivi Novianti

Bibliographic record

VenueJurnal PeWeKa Tadulako · 2024
Typearticle
Languageid
FieldEarth and Planetary Sciences
TopicGeological and Geophysical Studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Keberagaman Situs warisan geologi (geosite), baik yang terbentuk pasca 28 September 2018 maupun telah ada sebelumnya dapat dijadikan objek warisan Geologi (geoheritage) dalam suatu tatanan kawasan taman bumi (Geopark) yang memiliki ciri atau khas tertentu yang tidak terpisahkan dari sebuah cerita evolusi pembentukan suatu daerah. Berangkat dari pentingnya Kepariwisataan Berkelanjutan sesuai sasaran pembangunan dalam aspek konservasi, edukasi dan pembangunan perekonomian yang berkaitan erat dengan pengetahuan geodiversity dan geoheritage, yang menjadi alasan penting untuk melestarikan geoheritage diperlukan peran serta masarakat dan pemangku kepentingan terkait, termasuk dari komunitas geosains [6], maka diperlukan penilaian terhadap sumberdaya geologi Palukoro di Lembah Palu sebagai Langkah awal upaya pelestarian dan konservasi dalam mendukung pengembangan dan pemanfaatan geowisata secara berkelanjutan, dengan sasaran Penilaian sumberdaya warisan geologi yang ada di lembah Palu; dan Penilaian kelayakan geosite dalam pengembangkan geowisata di Lembah Palu yang dapat dimanfaatkan disegala aspek, diantaranya memberikan dasar ilmiah sebagai Upaya pelestarian warisan geologi, memudahkan penetapan prioritas konservasi berdasarkan nilai geologis dalam memanfaatkannya secara berkelanjutan yang terintegrasi dengan kegiatan pendidikan dan pengembangan ekonomi masyarakat yang bertumpu pada kegiatan geowisata [6].

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), 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 score0.375
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.042

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 head0.016
GPT teacher head0.219
Teacher spread0.203 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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