MétaCan
Menu
Back to cohort
Record W2259145336 · doi:10.5539/mas.v10n1p161

Institutional System of Watershed Management in Leitimor Peninsula, Ambon Island (Watershed Management Institution in Ambon Island Peninsula Leitimor)

2015· article· en· W2259145336 on OpenAlexvenueno aff
Jusmy D. Putuhena, Asep Sapei

Bibliographic record

VenueModern Applied Science · 2015
Typearticle
Languageen
FieldMedicine
TopicMangiferin and Mango Extracts
Canadian institutionsnot available
Fundersnot available
KeywordsWatershedWatershed managementDecentralizationInstitutionBusinessStakeholderEnvironmental resource managementPeninsulaEnvironmental planningGeographyPolitical scienceEnvironmental scienceComputer science

Abstract

fetched live from OpenAlex

Regional decentralization has made a change to any development sectors where a region (regency/town) holds a broader authority in managing natural resources, including watershed. Watershed management will run well if there is coordination and policy integration between the central and local government and between related institutions within a region. Relationship between institutions shall be always built on a coordination in order to prevent overlapping and conflict of interest in watershed management. The study aims to collect the data/information on main duties and functions of, authority of and roles of watershed management institution, especially the watershed in Ambon City, Leitimor Peninsula and to analyze them through stakeholder analysis approach. The findings found seventeen stakeholders who are in charge of the watershed management. Among those stakeholders, the primary and most important watershed managers are the Watershed Forum and forest farmer group.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.025
GPT teacher head0.261
Teacher spread0.236 · 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 designNot applicable
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

Citations3
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueModern Applied ScienceSame topicMangiferin and Mango ExtractsFrench-language works237,207