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Record W4412790500 · doi:10.14710/jil.23.4.896-906

Determinasi Perubahan Volume Air Terhadap Nilai Parameter Kualitas Air Pada Sumur Gali Masyarakat Di Kelurahan Fitu - Kota Ternate Selatan

2025· article· en· W4412790500 on OpenAlexaff
Salnuddin Salnuddin, Nurhalis Wahidin, Halima Malaka, Nida Humaida, Muhammad Said Alhadad, Asmar Hi Daud

Bibliographic record

VenueJurnal Ilmu Lingkungan · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicArchitectural and Urban Studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsVolume (thermodynamics)Physics

Abstract

fetched live from OpenAlex

Groundwater quality degradation in small volcanic islands presents complex challenges for freshwater availability, particularly where communities heavily rely on groundwater resources. A study of groundwater dynamics in dug wells on Ternate Island, Indonesia, examined the relationship between water volume changes and water quality parameters while evaluating seawater intrusion potential through hydrostatic balance analysis. Researchers measured physical parameters (temperature, surface pressure) and chemical parameters (salinity, dissolved oxygen, electrical conductivity, total dissolved solids) in three sample wells and one coastal point. The analysis incorporated calculations of water volume changes, flushing rates, and regression analysis between water volume changes and water quality parameters to assess the dynamics of groundwater quality fluctuations. Water level changes showed a 27-minute lag after tidal shifts, with well 1 showing dominant volume changes during ebb tide (65%), while wells 2 and 3 were dominant during flood tide. Well 2 showed higher susceptibility to quality changes due to its lower flushing rate (13.7%) compared to well 1 (56.6%). Statistical analysis revealed that water volume increases did not significantly influence water quality changes (p > 0.05). These findings enhance our understanding of groundwater dynamics in volcanic islands and suggest that factors beyond water volume changes should be considered when managing groundwater resources in these settings. The research provides valuable insights for developing effective water resource management strategies in similar geological contexts worldwide.

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), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.734
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.022
GPT teacher head0.247
Teacher spread0.225 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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