MétaCan
Menu
Back to cohort
Record W2275842118 · doi:10.30835/2413-7510.2015.57414

Визначення агроекологічної належності сортів рису в умовах затоплення

2015· article· en· W2275842118 on OpenAlexaboutno aff
В. О. Скидан

Bibliographic record

VenuePlant Breeding and Seed Production · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Productivity and Crop Improvement
Canadian institutionsnot available
Fundersnot available
KeywordsRipenessTemperate climateFlooding (psychology)AgronomyWaxGeographyBiologyEcologyBotanyRipening

Abstract

fetched live from OpenAlex

Selection of optimum rice varieties in different soil and climatic conditions is a prerequisite for the efficient use of natural resources to form highly productive crops. The aim and tasks of the study. The aim of our study was to determine the suitability of rice varieties for cultivation, depending on the climatic conditions of a region. Material and methods. The investigations were carried out at the experimental field of the Institute of Rice NAAS in 2011-2013 in compliance with the BA Dospekhov’s methodology of experimentation Results and discussion. The results of studying peculiarities of determination of agro-ecological affiliation of rice varieties in flooding conditions on different nutrition. Three types of agro-ecological affiliation of rice varieties were developed: northern, temperate and southern. If rice grain filling in rice varieties the most actively occurs in the phase of milk ripeness and virtually stops at the beginning of the phase of wax ripeness, these varieties can be referred to the northern type. If grain filling the most actively takes place in the phase of milk ripeness and the first half of the phase of wax ripeness and stops at the beginning of the second half of the phase of wax ripeness, these varieties can be referred to the temperate type. If grain filling is uniform during the phase of milk ripeness and until the end of the phase of wax ripeness, such varieties can be referred to the southern type. Conclusions. Variety ‘Debut’ belongs to the northern agro-ecological type; ‘Ontario’ – to the temperate type; and ‘Admiral’ - to the southern type.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.697
Threshold uncertainty score0.354

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.053
GPT teacher head0.196
Teacher spread0.142 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

Explore more

Same venuePlant Breeding and Seed ProductionSame topicAgricultural Productivity and Crop ImprovementFrench-language works237,207