MétaCan
Menu
Back to cohort

Kajian Keterawatan Lukisan Gua Prasejarah di Kawasan Karst Maros Pangkep Sulawesi Selatan

2016· article· id· W2965508881 on OpenAlexaff
Yadi Mulyadi

Bibliographic record

VenueJurnal Konservasi Cagar Budaya · 2016
Typearticle
Languageid
FieldArts and Humanities
TopicMaritime and Coastal Archaeology
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsHumanitiesPhysicsForestryGeographyArt

Abstract

fetched live from OpenAlex

Lukisan gua prasejarah di kawasan karst Maros Pangkep merupakan cagar budaya yang rentan dengan kerusakan, baik karena faktor alam maupun budaya. Oleh karena itu, kajian mengenai keterawatan lukisan gua prasejarah di kawasan ini penting untuk dilakukan guna memperoleh data yang akurat terkait tingkat kerusakan lukisan pada masing-masing gua. Metode penelitian arkeologi yang dipadukan dengan pendekatan lingkungan dan konservasi, menjadi panduan dalam kajian ini. Metode penelitian arkeologi dioperasionalkan dalam bentuk pengumpulan data, pengolahan data dan interpretasi data. Adapun pendekatan lingkungan dan konservasi diterapkan dalam observasi flora fauna dan bentang alam kawasan. Jumlah gua yang menjadi objek kajian yaitu 44 gua dengan rincian 24 gua di Maros dan 20 gua di Pangkep. Berdasarkan kajian yang dilakukan, tingkat keterawatan lukisan gua di kawasan karst Maros Pangkep ini bervariasi mulai dari sedang sampai parah, dan hanya lima gua yang kondisi keterawatan lukisan guanya bagus. Hal ini mengacu pada tingkat kerusakan dan pelapukan fisik (retak, pecah, aus), pelapukan biologis (pertumbuhan algae, moss, lichen), pelapukan kimiawi (penggaraman, sementasi), yang juga dipengaruhi oleh faktor alam dan faktor manusia.Oleh karena itu untuk mempertahankan tingkat keterawatan lukisan gua prasejarah diperlukan sebuah sistem konservasi gua prasejarah yang memadukan antara konservasi lingkungan, konservasi arkeologis dan juga pengelolaan sumberdaya arkeologi yang berbasis pelestarian.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.777
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 studies0.0020.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.004

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 head0.018
GPT teacher head0.218
Teacher spread0.199 · 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 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

Citations12
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJurnal Konservasi Cagar BudayaSame topicMaritime and Coastal ArchaeologyFrench-language works237,207