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Record W3082984041 · doi:10.5539/mas.v14n9p69

Soil Quality and the Selection of Physicochemical Properties around Maro Rivers in Merauke Papua

2020· article· en· W3082984041 on OpenAlexvenueno aff
Sumani Sumani, Supriyadi Supriyadi, Siti Masiyah, Widya Aryani

Bibliographic record

VenueModern Applied Science · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Land Suitability Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsMangroveTotal organic carbonEnvironmental scienceOrganic matterSoil waterNutrientSoil qualityHydrology (agriculture)Water contentSoil testAgricultureSoil organic matterInceptisolEcologySoil scienceGeologyBiology

Abstract

fetched live from OpenAlex

Merauke Regency has 216.196 Ha of mangroves area which most of it was fed by the Maro River. The purpose of this research was to study the chemical, nutrient movement, and physiochemical properties by collecting the soil around the Maro River. 10 collected soil samples (0-20 cm depth) were analyzed using standard methods. The result showed that the average CEC of soils around River Maro is 15.95 cmol/kg. Organic matter and soil moisture content could be the contributor to enhance the CEC of soil. The average organic carbon was 1.34%, while the BOD and COD were 2.44 and 5.70 mg/L. Soil could have different mineralogical content which nutrient around Maro is decreasing due to waste disposal to the river, agricultural practice, and other human activities. Environmental management needs to reevaluate and studies about soil mineralogy strongly recommended.

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 score0.013
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.026
GPT teacher head0.227
Teacher spread0.201 · 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
Published2020
Admission routes1
Has abstractyes

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