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Record W4413676848 · doi:10.3103/s1068367425700399

Study of Collection Samples of Oil Flax in the Conditions of the Southern Forest–Steppe of the Middle Volga Region

2025· article· en· W4413676848 on OpenAlexaboutno aff
А. В. Казарина, A. S. Shishina

Bibliographic record

VenueRussian Agricultural Sciences · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Industry and Aquatic Biology
Canadian institutionsnot available
Fundersnot available
KeywordsVolga regionPlant biochemistryForest steppeSteppeGeographySamaraAgroforestryForestryEnvironmental scienceBotanyArchaeologyBiologyAncient historyHistory

Abstract

fetched live from OpenAlex

Abstract The studies were conducted to examine collection samples of oil flax for the main economically valuable traits and to identify the most promising genotypes for involvement in the breeding process. The study was conducted in 2021–2023 in the conditions of the south of the forest–steppe zone of the Middle Volga region. The objects of research are 67 collection samples of oil flax of various ecological and geographical origins. The Kinelsky 2000 variety is taken as the standard. The soil of the experimental plot is typical medium-humus medium-deep medium-clayey chernozem. As a result of the study, the collection samples were differentiated into groups based on the main economically valuable traits that determine the technological effectiveness and productivity of flax (duration of the growing season, total plant height, weight of 1000 seeds, seed yield, elements of the crop structure) in accordance with the broad unified classifier of the CMEA species Linum usitatissium L. (flax). Over the years of study, promising accessions were selected for inclusion in breeding programs as genetic sources of valuable traits: six accessions ripening 5–8 days earlier than the standard were selected based on early maturity; eight accessions exceeding the standard variety by 3.6–13.5% based on plant height; 11 accessions exceeding the standard by 43.8–87.0% based on the number of productive capsules per plant; seven accessions exceeding the standard by 16.9–23.1% based on the number of seeds per capsule; six accessions exceeding the standard by 4.4–16.9% based on the weight of 1000 seeds. Sixteen collection samples were selected (VNIIMK 620, k-4921 (Tajikistan), k-4989 (Ukraine), k-6497 (Kazakhstan), k-6511 (Kazakhstan), KinxL/2009k, Kinx W/2009k, L-405/2020, Cian (Russia), 27 A-9 (Russia), Betking (Germany), Hindukusz (Afghanistan), Kaufmann (Germany), N.P 84 (India), Ottawa 5648-M (Canada), Р 6909 (Czech Republic)) possessing a set of economically valuable traits, the yield of which over the years of research was in the range of 207.8…244.7 g/m2, which is 12.1…32.1% higher than the standard.

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 score0.129
Threshold uncertainty score0.879

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.066
GPT teacher head0.245
Teacher spread0.179 · 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
Published2025
Admission routes1
Has abstractyes

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