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Record W1833245318 · doi:10.5376/ijms.2012.02.0003

The Economic Valuation and the Use of Mangrove Resource at the Coast of Pangkep District, South Sulawesi Province

2012· article· en· W1833245318 on OpenAlexvenueno aff
Tantu Andi Gusti

Bibliographic record

VenueInternational Journal of Marine Science · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Agroindustry Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMangroveValuation (finance)GeographyContingent valuationResource (disambiguation)ForestryFisheryBusinessEconomicsWillingness to payBiology

Abstract

fetched live from OpenAlex

Research was conducted on January 2012. The aim of the research was to the economic valuation and the use of mangrove resource at the coast of Pangkep District, South Sulawesi, Indonesia. Survey research approach was used in this research and data were analyzed descriptively and quantitatively. The result showed that mangroves were utilized for capture fisheries, and wood sources. Economic value of mangrove was Rp.58 467 828.24/ha/year. Capture fisheries are the largest contribution, up to 97.8 percent. Mangrove is the most important income source for society in Pangkep coast who live in the vicinity. Therefore coastal management policy was required to be developed by considering the impact on socio economics of mangrove utilization on community at Pangkep coast, especially related to coastal utilization area change.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.033
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.231
Teacher spread0.196 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2012
Admission routes1
Has abstractyes

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