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Record W2947334171 · doi:10.5539/jas.v11n8p295

Syzygium aromaticum Essential Oil to the Control of Tenuipalpus heveae

2019· article· en· W2947334171 on OpenAlexvenueno aff
Thalia Mayara Pereira de Melo, Eliamara Marques da Silva, Abimael Gomes da Silva, Gustavo Haralampidou da Costa Vieira, Beatriz Garcia Lopes

Bibliographic record

VenueJournal of Agricultural Science · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect Pest Control Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsSyzygiumHorticultureEssential oilToxicologyTenuipalpidaeBiologyMiteAnimal scienceBotany

Abstract

fetched live from OpenAlex

The objective was to determine the effect of essential oils on the mortality and repellency of the Tenuipalpus heveae Baker mite (Acari, Tenuipalpidae). Leaf discs of rubber trees were deposited in Petri dishes containing a moistened cotton layer. Posteriorly, the essential oils were diluted to formulate solutions, which were sprayed onto the discs. The experimental design was completely randomized, in a 3 × 4 factorial design: neem, cedar and clove oils at doses 0, 10 μL, 50 μL and 100 μL, with five replicates, with ten adult females being considered per replicate. The exposure to the effect of essential oil was evaluated after 24, 48, 72 and 96 hours for the number of females dead and females in the cotton. The data were submitted to analysis of variance, the values were transformed into (x + 0.5)1/2, and the means were grouped by the Scott-Knot test at 5% probability for the treatments, the doses were submitted to regression analysis. From the 48 hours of evaluation, clove oil showed greater potential for adult mite mortality, being 1.38 in 48 hours, 1.40 in 72 hours and 1.50 in 96 hours. The dose of 100 μL presented a greater potential for the neem and clove oils. The clove essential oil has potential in the control of Tenuipalpus heveae.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.006
GPT teacher head0.199
Teacher spread0.193 · 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.

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

Citations5
Published2019
Admission routes1
Has abstractyes

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