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Record W2625689922 · doi:10.5539/sar.v6n3p75

Nitrous Oxide Emission of a Tropical Peat Soil Grown with Pineapple at Saratok, Malaysia

2017· article· en· W2625689922 on OpenAlexvenueno aff
Liza Nuriati Lim Kim Choo, Osumanu Haruna Ahmed

Bibliographic record

VenueSustainable Agriculture Research · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsnot available
FundersInstitut Penyelidikan dan Kemajuan Pertanian MalaysiaUniversiti Putra MalaysiaMinistry of Higher Education, Malaysia
KeywordsPeatNitrous oxideSoil waterEnvironmental scienceSoil respirationAgronomyLysimeterHistosolChemistryEnvironmental chemistrySoil scienceSoil organic matterSoil biodiversityEcology

Abstract

fetched live from OpenAlex

Draining of peatland for agriculture could affect the release of nitrous oxide into the atmosphere. Presently, there is dearth of information on soil nitrous oxide emission from tropical peat soils cultivated with pineapples. Lysimeter and closed chamber methods were used to quantify nitrous oxide emission from root respiration, microbial respiration, and oxidative peat decomposition under controlled water table condition. Treatments evaluated were: peat soil grown with pineapple, uncultivated peat soils, and bare peat soil fumigated with chloroform. Cultivation of Moris pineapple on drained peat soils resulted in the higher release of nitrous oxide emission (15.7 t N2O ha/yr), followed by fumigated peat soil with chloroform (14.3 t N2O ha/yr), and uncultivated peat soil (10.2 t N2O ha/yr). Soil nitrous oxide emission was affected by nitrate fertilization but emission was not affected by soil temperature nor soil moisture.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.040

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)0.0000.000

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 head0.013
GPT teacher head0.272
Teacher spread0.259 · 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
Published2017
Admission routes1
Has abstractyes

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