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Record W4409345909 · doi:10.18280/ijdne.200313

Environmental-Friendly Agricultural Practices and Soil Conservation: A Case Study of Herbicides Use in the Gayo Highlands

2025· article· en· W4409345909 on OpenAlexvenueno aff
Raichan Izzati, Abubakar Karim, Hifnalisa Hifnalisa, Hasanuddin Hasanuddin

Bibliographic record

VenueInternational Journal of Design & Nature and Ecodynamics · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsnot available
Fundersnot available
KeywordsAgricultureEnvironmentally friendlyAgroforestryEnvironmental scienceEnvironmental resource managementEnvironmental protectionEcologyBiology

Abstract

fetched live from OpenAlex

Results from International Laboratory Research indicate that Gayo Arabica coffee contains glyphosate chemical residues that exceed permissible limits.Specifically, glyphosate residues were found to exceed the maximum limit of 0.1 mg/kg, as set by the WHO/FAO.The implementation of environmentally friendly agricultural practices is essential to promote soil health.This investigation represents the first systematic study utilizing a stratified random sampling questionnaire.This study aims to identify the distribution, active ingredients, dosage, and regulation of herbicide use in the Gayo Highlands region, covering 81,541.38 hectares.In this study, 101 out of 200 Arabica coffee farmers were found to use herbicides, with two types of active ingredients and 22 commercial brands, each with varying concentrations and application regulations.Notably, glyphosate was the most commonly used active ingredient, represented by 18 different commercial brands.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.069

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 studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
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 head0.021
GPT teacher head0.275
Teacher spread0.254 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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