MétaCan
Menu
Back to cohort
Record W2121253329 · doi:10.5539/mas.v8n4p1

Effects of Tillage System and Soil Organic Matter Amendment on Growth, Yield of Pathumthani 80 Rice and Carbon Sequestration in Paddy Soil

2014· article· en· W2121253329 on OpenAlexvenueno aff
Kanyarat Buarach, Chaisit Thongjoo, Nawarat Udomprasert, Suphachai Amkha

Bibliographic record

VenueModern Applied Science · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsnot available
FundersKasetsart University
KeywordsTillageAgronomySoil carbonAmendmentEnvironmental scienceNo-till farmingSesbaniaSoil organic matterOrganic matterConventional tillageSoil waterSoil fertilitySoil scienceChemistryBiology

Abstract

fetched live from OpenAlex

This study was conducted to determine the effect of tillage systems and soil organic amendments on rice growth, yield and carbon sequestration on paddy soil. The experiment was conducted by using 2x4 factorials in complete randomized design. The first factor was tillage systems (conventional tillage; to and minimum tillage; t1) and the second factor was soil organic amendments (mungbean; p0, sesbania; p1, sunhemp; p2 and rice straw; p3). The results demonstrated that adding organic matter derived from mungbean to the soil was the highest and significantly different of plant height and carbon stock in rice (P?0.01). The tillage system and organic matter amendment was not significantly different of rice yield. However, tillage systems with a mungbean amendment tent to increased the rice yield. Soil organic matter was the highest in sumhep amendment in soil as following by sesbania, mungbean and rice straw, respectively. In addition, minimum tillage system can increase carbon sequestration in soil at 15 cm soil depth (P?0.01).

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.203
Threshold uncertainty score0.210

Codex and Gemma teacher scores by category

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 head0.007
GPT teacher head0.177
Teacher spread0.170 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations6
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueModern Applied ScienceSame topicSoil Carbon and Nitrogen DynamicsFrench-language works237,207