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Record W3182659595 · doi:10.5539/jas.v13n8p16

Essential Oil Variation in Brazilian Varronia curassavica Jacq. in Response to Drying and Edaphoclimatic Conditions

2021· article· en· W3182659595 on OpenAlexvenueno aff
Teomar Duarte da Silva, Michele Trombin de Souza, Mireli Trombin de Souza, Roger Raupp Cipriano, H. R. Bizzo, Cícero Deschamps

Bibliographic record

VenueJournal of Agricultural Science · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEssential Oils and Antimicrobial Activity
Canadian institutionsnot available
Fundersnot available
KeywordsSabineneEssential oilBotanyChemical compositionHumuleneBiologyHorticultureChemistryOrganic chemistryLimonene

Abstract

fetched live from OpenAlex

Varronia curassavica Jacq. (Boraginaceae) is a native species of the Atlantic Forest with medical importance. This study determined the essential oil variation of 16 populations of V. curassavica of restinga in Santa Catarina, Brazil, in response to drying and edaphoclimatic conditions. The populations supplied essential oil with a content between 0.27 to 1.15% in the summer and from 0.33 to 1.12% in the winter. 41 chemical compounds were identified in the summer and 40 in the winter. The compounds were grouped into 4 chemical classes in each station studied. The common chemical constituents found in the essential oil of all populations and in both seasons were α-thujene, α-pinene, sabinene, α-humulene, (E)-cariophylene, spatulenol, mircene, allo-aromadendrene, β-sesquifelandreno and α-zingiberene. Cluster analysis using the nearest neighbor method based on Euclidean distance grouped the 16 populations into 3 groups in the summer and 8 groups in the winter. As the habitats have distinct pedological characteristics, we identified that pH, organic matter, sum of bases and base saturation are associated with the synthesis of (E)-caryophyllene, α-humulene, and allo-aromadendrene from populations.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.008
GPT teacher head0.242
Teacher spread0.234 · 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 designObservational
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
Published2021
Admission routes1
Has abstractyes

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