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Research Concerning the Fighting of Polystigma rubrum Fungi under the Climate Conditions of Șomcuta Mare Area

2019· article· en· W3022892317 on OpenAlexaff
Lucia Mihălescu, Monica Marian, Stela Jelea, Flavia Pop, Aurel MAXIM, Zorica Voșgan

Bibliographic record

VenueBulletin of University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca Agriculture · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Physiology and Cultivation Studies
Canadian institutionsScience North
Fundersnot available
KeywordsFungicideVariety (cybernetics)Product (mathematics)HorticultureBiologyBotanyEnvironmental scienceToxicologyMathematicsStatistics

Abstract

fetched live from OpenAlex

In this study, our goal was to survey the influence of the climate conditions, the behavior of the Centenar and Anna Spath varieties on the attack of the Polystigma rubrum fungi during the two experimental years (2013, 2014), in order to make recommendations for new plantations. Nine fungicides were tested, being determined their biologic efficiency, in order to identify the most efficient products. The experimental research was performed during 2013 and 2014, in a fruit tree farm belonging to SC Pomicola SA trade company in Somcuta Mare, Maramures county. The attack was calculated by determining the frequency, intensity and the attack degree. The agrometeorological data were recorded using the AgroExpert system, for surveying the biology of fungi. The linear-interrupted laying method was used, each made up of 5 plants/variant in three repetitions/product. The biologic efficiency of the tested products was lower at the Anna Spath variety than at the Centenar variety due to its sensitivity; the recommended products: Folicur Solo 250EW, Dithane M45 and Syllit 400 SC were the most efficient in the fungi combating.

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)0.001
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 score0.969
Threshold uncertainty score0.676

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.067
GPT teacher head0.265
Teacher spread0.199 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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