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Record W4246986291 · doi:10.1094/phyto-107-12-s5.196

Abstracts of Presentations at the 2017 Northeastern Division Meeting

2017· article· en· W4246986291 on OpenAlexaff
R. A. Majeed, Ahmad Ali Shahıd, Mathews L. Paret, Muhammad Akhter, Muhammad Haider, Kelly‐Ann Allen, Genevieve Higgins, Li‐Jun Ma, Robert L. Wick, Guillaume J. Bilodeau, Odile Carisse, Maryse Gendron, Valérie Gravel, Mamadou L. Fall

Bibliographic record

VenuePhytopathology · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsCanadian Food Inspection AgencyMcGill UniversityAgriculture and Agri-Food Canada
Fundersnot available
KeywordsBiologyDivision (mathematics)Library scienceComputational biologyEvolutionary biologyComputer scienceArithmetic

Abstract

fetched live from OpenAlex

Rice brown spot produced by Bipolaris oryzae Breda de Hann (formely, Helminthosporium oryzae) (telemorph = Cochliobolus miyabeanus) is considered as important production restraint of rice and occurred in all rice-growing areas of the world.Essential oils obtained from Lemongrass and Eucalyptus leaves were checked for their antifungal potentials against Bipolaris oryzae.Selected essential oils were checked in different concentrations of 1000 ppm, 500 ppm, 250 ppm and 150 ppm for their ability to inhibit the growth of the test fungi in-vitro and also in-vivo.The in-vitro and in-vivo studies revealed that the essential oils of lemongrass have the potential to inhibit the growth of test fungi completely at all concentrations.Essential oils of Lemongrass were more effective than Eucalyptus.Formulating a Bio-Fungicide from these essential oils provide a more safer and Eco-friendly control of Brown Spot of Rice as it is an emerging disease in all rice growing areas of the world.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.515
Threshold uncertainty score0.692

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.5150.245

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 head0.022
GPT teacher head0.289
Teacher spread0.266 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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
Published2017
Admission routes1
Has abstractyes

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