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Record W2773851435 · doi:10.5539/mas.v12n1p1

Potential of Mangrove Apples (Sonneratia alba) as a Botanical Insecticide

2017· article· en· W2773851435 on OpenAlexvenueno aff
Victor George Siahaya, Trijunianto Moniharapon, Meigy Nelce Mailoa, Johanna Audrey Leatemia

Bibliographic record

VenueModern Applied Science · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicAgricultural and Environmental Management
Canadian institutionsnot available
Fundersnot available
KeywordsPhytochemicalMangroveNezara viridulaBiologyFlavonoidLarvaBotanyTraditional medicineHorticultureEcologyAntioxidantMedicine

Abstract

fetched live from OpenAlex

This study aims to determine the potential of mangrove apple extract (Sonneratia alba) as a botanical insecticide. Tests were conducted to observe the bioactivity of mangrove apple extract and phytochemical tests were conducted in order to see the content of bioactive compounds. The test results showed that the mortality rate of test larva (Nezara viridula) reached 98%, while the phytochemical test showed that the mangrove fruit contains phytotoxin compounds that can affect the behavior and even kill the test larvae. The compounds found are flavonoids, triterpenoids, alkaloids, tannins, steroids, phenolics, and saponins. The influence of flavonoid compounds is strong enough to attract insects.

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 score0.004

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 head0.014
GPT teacher head0.266
Teacher spread0.253 · 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

Citations16
Published2017
Admission routes1
Has abstractyes

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