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Record W3177912108

Изучение и подбор исходного материала сои для создания новых сортов

2018· article· ru· W3177912108 on OpenAlexaboutno aff
Е. В. Гуреева

Bibliographic record

VenueАграрная наука · 2018
Typearticle
Languageru
FieldAgricultural and Biological Sciences
TopicSoybean genetics and cultivation
Canadian institutionsnot available
Fundersnot available
KeywordsRipenessGeographyHorticultureProductivityBiologyForestryAgronomyAgricultural scienceRipening
DOInot available

Abstract

fetched live from OpenAlex

The article presents the results of the study on more than 200 varieties of soybean of different ecological and geographical origin. The samples were taken from the collections of All-Union Research Institute of Plant Breeding. The study was conducted in the Ryazan region in 2015-2017. As a result of the study, there were developed varieties with increased productivity and optimal duration of vegetation period. The varieties had an increased number of beans and seeds, high protein content in seeds and high oil content. The correlation analysis revealed that the duration of vegetation period was mostly determined by the value of blossom - full ripeness”, r = 0.811, and to a lesser extent the duration depended on germinated - full blossom”, r = 4.482. The best samples were Kastka (Ryazan region), Chera 1 (Chuvashia), Merlin (Austria), Elena (Ukraine), Semu 315 (Germany), Gaillard (Canada). These samples will be included in the selection process as initial materials, in order to develop high-yield soybean varieties adapted to the Central region of Russia.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.003

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 head0.029
GPT teacher head0.232
Teacher spread0.203 · 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 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
Published2018
Admission routes1
Has abstractyes

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