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Record W3047885711 · doi:10.1016/j.ejrh.2020.100716

Hydrogeochemical processes and long-term effects of sea-level rise in an uplifted atoll island of Minami-Daito, Japan

2020· article· en· W3047885711 on OpenAlexaff
Heejun Yang, Makoto Kagabu, Azusa Okumura, Jun Shimada, Tomo Shibata, Daniele L. Pinti

Bibliographic record

VenueJournal of Hydrology Regional Studies · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGroundwater and Isotope Geochemistry
Canadian institutionsUniversité du Québec à Montréal
FundersJapan Science and Technology Agency
KeywordsGroundwaterSeawaterAtollSalinityDolomiteGeologyδ18OAquiferCalciteHydrology (agriculture)GeochemistryOceanographyStable isotope ratioSurface waterEnvironmental science

Abstract

fetched live from OpenAlex

An uplifted atoll of Minami-Daito Island, Japan. Major ions and stable isotopes (δ2H and δ18O) of groundwater at fifteen observation wells, surface water at eight representative lakes and one seawater site were measured to unravel the dominant processes controlling the chemistry of water, its spatial distribution and to identify the salinization mechanism caused by long-term sea-level rise. Rainfall is the main source for groundwater and lake water. Evaporation affects both the ion concentration and the stable isotopes of the lake water. Geochemical modeling suggests that freshwater-seawater mixing is the main process increasing concentrations of Na+, Cl−, Mg2+, and SO42−, whereas dissolution of calcite and dolomite increases concentrations of Ca2+, Mg2+, and HCO3− in groundwater. Fresh groundwater and lake water (i.e., Cl− < 500 mg/L) are largely distributed along a SW-NE direction, but they have been reduced since the 1970s. Sea-level rise causes an increase in the salinity of lake water by flowing through fractures being connected from lakes to the northern coast, then spreading to other lakes through the artificial channels built in the years.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.431

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.031
GPT teacher head0.253
Teacher spread0.222 · 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

Citations14
Published2020
Admission routes1
Has abstractyes

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