MétaCan
Menu
Back to cohort
Record W4386754143 · doi:10.18280/ijdne.180410

Environmental Impact Assessment of Rice Growing in the Kyzylorda Region

2023· article· en· W4386754143 on OpenAlexvenueno aff
Lyailya Akbayeva, Kuralay Mukanova, Raikhan Beisenova, Rumiya Tazitdinova, Nazira Kobetaeva

Bibliographic record

VenueInternational Journal of Design & Nature and Ecodynamics · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Biological Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental impact assessmentEnvironmental scienceEngineeringBiologyEcology

Abstract

fetched live from OpenAlex

In the context of the growing ecological crisis caused by climate change, irrational use of water resources and environmental pollution with dangerous pollutants, an important role is played by assessing the role of environmental damage from crop production.The authors analyzed the environmental compatibility of modern rice production in the main rice growing region in the Republic of Kazakhstanthe Kyzylorda region.The work included theoretical calculations of methane greenhouse gas emissions throughout the region for the entire vegetative season.And also calculated the costs of water resources for irrigation of rice fields, including water leaving for evaporation from the water surface, evapontranspiria, saturation of the soil, filtration flow and outflow into the drainage network.In the grain of rice varieties "Aikerim" and "Favorit" grown in the Kyzylorda region, residual amounts of such toxic substances as organochlorine pesticides (HCH α, β, γ-isomers, DDT, DDE) were determined.Heavy metals (cadmium, lead, arsenic and mercury) were also determined in these varieties of rice.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.533
Threshold uncertainty score0.123

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 head0.019
GPT teacher head0.267
Teacher spread0.248 · 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 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Design & Nature and EcodynamicsSame topicAgriculture and Biological StudiesFrench-language works237,207