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Record W4381740475 · doi:10.26898/0370-8799-2023-5-5

Evaluation of oat varieties adaptive properties by productivity in the Priobskaya forest-steppe zone

2023· article· en· W4381740475 on OpenAlexaboutno aff
A. Ya. Sotnik

Bibliographic record

VenueSiberian Herald of Agricultural Science · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Productivity and Crop Improvement
Canadian institutionsnot available
FundersSiberian Branch, Russian Academy of Sciences
KeywordsAdaptabilityRipenessProductivityPhenologySteppeYield (engineering)Forest steppeAgronomyRussian federationResearch ObjectGrowing seasonBiologyGeographyHorticultureEcologyRipening

Abstract

fetched live from OpenAlex

The results of evaluation of adaptive properties of released oat varieties of Siberian breeding by yield in the Priobskaya forest-steppe of Novosibirsk region are presented. The experiment was conducted on the experimental field of the Siberian Research Institute of Plant Production and Breeding in 2012-2021. The object of the study were 37 oat varieties included in the State Register of the Russian Federation and released in the West Siberian (№ 10) and East Siberian (№ 11) regions. Yield estimation and phenological observations were carried out according to the methodology of N.I. Vavilov All-Russian Institute of Plant Genetic Resources. For statistical data processing the method of B.A. Dospekhov was used. Potential productivity and adaptability of the varieties were determined by L.A. Zhivotkov et al. method, resistance of the varieties to stress conditions - by A.A. Goncharenko, the yield spread - by V.A. Zykin. Analysis of yields by groups of ripeness showed a natural tendency: as the growing season lengthens by groups of ripeness, the productivity potential also increases. The following varieties had high indicators of productivity potential in favorable years and adaptability to adverse environmental factors: Krasnoobsky, Mustang, Metis, Oven, Otrada, Talisman, Irtysh 21, SIR 4, Orion. The varieties Oven, Novosibirsk 5, CIR 4 showed high adaptability and stability. Four varieties were characterized by the ability to give not the maximum, but high stable yield under any conditions: Krupnozerny, Novosibirsk 88, Belozerny, and Korifey.

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)0.004
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 score0.860
Threshold uncertainty score0.279

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.048
GPT teacher head0.233
Teacher spread0.186 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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