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Record W4386031725 · doi:10.53555/sfs.v10i1.1471

Investigations On Anti- Termite Activity Of Eucalyptus Globulus Leaf Extract

2023· article· en· W4386031725 on OpenAlexvenueno aff
Umang Umang, Amit Kumar Kaundal, Poonam Kumari, Sukhvir Kaur

Bibliographic record

VenueJournal of Survey in Fisheries Sciences · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect and Arachnid Ecology and Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsEucalyptus globulusEucalyptusEucalyptus oilMyrtaceaePesticideToxicologyBiologyBotanyHorticultureAgronomy

Abstract

fetched live from OpenAlex

This study aims to investigate the anti-termite activity of eucalyptus globulus leaf extract. Termites are destructive pests that cause significant damage to wooden materials that ultimately leads to financial losses as well as structural instability. Natural remedies for termite control are gaining attention due to concerns over the environmental and health impacts of synthetic pesticides. The Ethanolic extract of Eucalyptus globulus leaves show 90% mortality rate at 2mg/ml concentration whereas essential oil shows 80% mortality rate at same concentration. This shows that, the Ethanolic extract of Eucalyptus globulus leaves were more effective as compared to the essential oil. So, this conveys that with increase in concentration, the mortality rate of termites also increases. This research show that both Ethanolic extract of Eucalyptus globulus leaves and essential oil shows excellent inhibitory activity against termites. These results will be helpful for future researchers for the development of potent, safe and cost effective pesticides.

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 head0.140
GPT teacher head0.312
Teacher spread0.171 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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