Correlation Between Mangrove and Aquaculture Production: Case Study in Sinjai District, Sulawesi, Indonesia
Bibliographic record
Abstract
Mangrove ecosystem generally accepted as nursery ground of variety if ahrimp and fish fries. The study has three objectives, namely to analyze the correlation (1) between mangrove percent ratio and primary product aquaculture, (2) between mangrove percent ratio and secondary product aquaculture, and (3) between direct benefit value mangrove ecosystem and coastal fisheries production. The research was carried out in Samataring village and Tongke village in East Sinjaisub-district, Sinjai district. Trend of fisheries data both from capture and aquaculture were analyzed, then compared with purposive sampling interview. Correlation and regression analysis were used to generate equations. The results of this research are as follows: (1) the correlation between mangrove ratio percentage and increased primary aquaculture produce negatively correlates and results in an equation of y=0.091x+8.800 with R 2 =0.99, (2) mangrove ratio percentage and increased secondary aquaculture produce are positively correlated and results in an equation of y=0.016x+0.239 with R 2 =0.99, and (3) Mangrove ecosystem direct benefit value and increased coastal catch produce positively correlate and result in an equation of y=0.485x-0.347 with R 2 =0.99.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".