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Record W3089866359 · doi:10.26898/0370-8799-2020-4-6

Resistance of samples of naked oats to stem rust

2020· article· en· W3089866359 on OpenAlexaboutno aff
О. А. Исачкова, А. О. Логинова

Bibliographic record

VenueSiberian Herald of Agricultural Science · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Productivity and Crop Improvement
Canadian institutionsnot available
Fundersnot available
KeywordsStem rustRust (programming language)BiologyHorticulturePlant disease resistanceAgronomySmutResistance (ecology)Veterinary medicineAnimal science

Abstract

fetched live from OpenAlex

The results of studying the resistance of samples of naked oats from the world collection of the N.I. Vavilov All-Russian Institute of Plant Genetic Resources and varieties of local breeding work to stem rust lesion are presented. The study was carried out in 20172019 in a field experiment in natural conditions in Kemerovo region. The influence of meteorological factors during the vegetation period of naked oat plants on the degree of disease damage was noted: more intense lesion was observed in years with low air temperatures and excessive moisture supply during the period of seedling-ear formation and a large amount of precipitation during the period of filling and maturation of grain. The results of phytopathological analysis of 50 collection samples of naked oats revealed that mid-late samples are more affected by stem rust (74.9% on average for the group). The study (n = 50) revealed the effect of stem rust lesion on the resistance to lodging of crops (r = –0.5751 at R = 0.273), grain size (r = –0.7737 at R = 0.273), and yield of naked oat samples (r = –0.9387 at R = 0.273). Naked oats are highly susceptible to pathogen lesion, 84% of the samples showed very low resistance with a damage index of more than 65.1%. Samples with a low damage degree were identified, characterized by high yield rates, 1000 grain weight, resistance to lodging and smut fungi, and a low level of segregation of hulled grains: Pennline 9010 (USA), Numbat (Australia), Progress (Omsk region), Gehl (Canada), Piband (Leningrad region), g/o-327-1/16, g/o-441-1/17, g/o-444-7/17 (Kemerovo region).

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.435
Threshold uncertainty score0.295

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 studies0.0000.000
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 head0.033
GPT teacher head0.210
Teacher spread0.177 · 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
Published2020
Admission routes1
Has abstractyes

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