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Record W4255142006 · doi:10.28930/jitkt.v3i1.7834

COASTAL VULNERABILITY PREDICTION TO CLIMATE CHANGE: STUDY CASE IN CIREBON COASTAL LAND

2011· article· en· W4255142006 on OpenAlexaff
Ricky Rositasari, Wahyu Setiawan, Indarto H. Supriadi, Hasanuddin Hasanuddin, Bayu Prayuda

Bibliographic record

VenueJurnal Ilmu dan Teknologi Kelautan Tropis · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geophysical Studies
Canadian institutionsWiLAN (Canada)
FundersGriffith UniversityUniversity of Cambridge
KeywordsGeographySea levelClimate changeLand areaSea level changeJavaPhysical geographyEnvironmental scienceHydrology (agriculture)OceanographyGeology

Abstract

fetched live from OpenAlex

<p>Coastal area is the most vulnerable area to climate change. Cirebon coastal land in Western Java, Indonesia is low-lying coastal area which is one of the potential areal for fish culture and farming. There are also major transportation facilities for western Java province to the whole area in the island (Java) through this area. As low-lying landscape, populated and developing city, Cirebon should be considered vulnerable to future sea level rise. Geomorphology, geo-electric and remote sensing study were conducted during 2008 and 2009 in coastal land of Cirebon. The result showed that most part of coastal area in Cirebon was eroded in various scales which vulnerable turn to worst. Sea water was penetrating throughout several kilometres inland. Valuation on various land-uses would project 1,295,071,755,150 rupiah/ha/year of loss while sea level were rose 0.8 meters that would inundate various land-uses i.e., Shrimp, fish and salt ponds, rice fields and settlement in the area.</p><p>Keywords: vulnerability, coastal, climate change, sea level rise</p>

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 score0.189
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.047
GPT teacher head0.242
Teacher spread0.195 · 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

Citations2
Published2011
Admission routes1
Has abstractyes

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