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Record W4283763072 · doi:10.18280/ijdne.170309

Identification of Karstification Zoning and Aquifer Channels in Karst Basin at Sendang Biru Beach, Malang-Indonesia: A Case Study

2022· article· en· W4283763072 on OpenAlexvenueno aff
Abdul Wahid, Sunaryo Sunaryo, Adi Susilo, Wiyono Wiyono

Bibliographic record

VenueInternational Journal of Design & Nature and Ecodynamics · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geophysical Studies
Canadian institutionsnot available
Fundersnot available
KeywordsKarstAquiferElectrical resistivity tomographyGeologyZoningGroundwaterGeomorphologyStructural basinCaveSinkholeGeochemistryHydrology (agriculture)Geotechnical engineeringPaleontologyElectrical resistivity and conductivityArchaeologyGeography

Abstract

fetched live from OpenAlex

Karst zoning and channel aquifers in the karst basin at Sendang Biru Beach, Tambak Rejo Village have been investigated. Sendang Biru Beach has a cave appearance as a karst morphological feature and is composed of limestone. Seasonal karst water sources come from springs, surface runoff, underground rivers, channels in valleys, basins, and slopes that often experience drought. The purpose of this study is to identify the presence of karst aquifers and karstification zones that are prone to damage or disasters in the karst environment. The method used is a geophysical combination of Electrical Resistivity Tomography (ERT), Induced Polarization (IP), and Self Potential (SP). The results showed that the eastern part's karstification zone was characterized by moderate to high resistivity and a chargeability zone with a moderate to high range. In addition, the existence of karst aquifer channels in the anomalous zone of low resistivity, high chargeability, and negative natural potential. This zone is located in the Qas Formation, with the water flowing from west to east and from west to south. The inundated karst aquifer that spreads in a circular pattern with different depths interspersed by limestone cracks causes a heterogeneous karstification process.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.291

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.235
Teacher spread0.221 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2022
Admission routes1
Has abstractyes

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