“Assessment of Coastal Vulnerability Index on potential agricultural land - CVI, Banyuwangi Regency”
Bibliographic record
Abstract
Indonesia is an archipelago country that has the longest coastline after Canada (UNCLOS). Banyuwangi District is a coastal area in Northern Java, which has a very dynamic development because of its location of the capital city that located along the coastal area. The purpose of this study is to assess the degree of coastal vulnerability in Banyuwangi District with the higher level of development. The CVI method (Coastal Vulnarability Index) of evisien sting is used to assess vulnerability. The coastal vulnerability is very low over 8 km, with a 15.4% of coastal length of Banyuwangi District. Low vulnerability occurs in areas that are located in areas close to settlements area, with beaches already experiencing human intervention. The low category is about 12 km long, reaching 23.3% of the existing coastal length in Banyuwangi District. The middle category is about 16 km, equivalent to 30.8% of shoreline. While the high category is about 10 km, equivalent to 19.2% of coastal length. The highest category has a length of 6 km, equivalent to 11.5% of the coastal area of Banyuwangi district.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".