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SNOW MOLDS: HISTORY OF THE STUDY AND CONTROL

2015· article· en· W2327701202 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSel skokhozyaistvennaya Biologiya · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicTurfgrass Adaptation and Management
Canadian institutionsnot available
Fundersnot available
KeywordsSnowControl (management)Physical geographyGeographyComputer scienceMeteorologyArtificial intelligence

Abstract

fetched live from OpenAlex

Snow mold is caused by pathogenic low-temperature fungi and fungi-like pathogens which can attack grassy winter and perennial plants and even woody plants. Pathogens infect crops in autumn and develop under snow and early in spring at low temperatures. History of the emergence of the terminology for pathogenic low-temperature fungi, the appearance of the snow mold terms and domestic vyprevaniye (eng. dumping-off) are represented, and various snow molds and their pathogens in Russia are described. Recent advances in agrochemical, chemical, biological and breeding technologies used to provide snow mold control are under consideration in detail, particularly data obtained in North America (USA, Canada), North Europe (Sweden, Norway, Finland), Asia (Japan) with special attention to the investigations in Russia. Crop rotation using crops being not the host plants of these pathogens and thus resistant to them is considered as rather effective agrotechnology decreasing plant damage from snow molds, and also deep tillage, early or late sowing, show thawing by its covering with black materials, monthly use of some composts are also discussed. Seed sterilization against Microdochium nivale infection is widely used in North Europe. In Russia the Baytan, Benlat, Granoza and Pentiuram are used on winter crops against Typhula incarnata and T. idahoensis (syn. T. ishikariensis). Fungicides are economically effective in the years of strong damage from snow molds, at that, pathogenic species differ in sensitiveness to fungicides. Characteristics of definite fungicides used are discussed. Biological suppression also is a method for anti-snow mold protection. For the purposes, the antagonistic agents effective in summer when snow molds are dormant, as well as low temperature agents active in the period of snow mold development can be used. Natural suppressors such as composts and antagonistic organisms were successful against Typhula spp. No special breeding for plant resistance to snow molds was carried out in Russia until recent time, nevertheless, in numerous investigations some grain crop species resistant to snow mold have been revealed. Particularly, by immunological assessment of 500 specimens from the VIR World Collection (N.I.

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.

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 score0.229
Threshold uncertainty score0.279

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.027
GPT teacher head0.210
Teacher spread0.184 · 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