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Record W2139315155 · doi:10.1002/ptr.1516

The chemical composition of some Lauraceae essential oils and their antifungal activities

2004· article· en· W2139315155 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePhytotherapy Research · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEssential Oils and Antimicrobial Activity
Canadian institutionsInstitute for Biological Sciences
FundersScience and Engineering Research Board
KeywordsLauraceaeCinnamomum zeylanicumEssential oilLinaloolLaurus nobilisSafroleBiologyBotanyTraditional medicineCinnamomumAntifungalCinnamaldehydeFood scienceChemistryMicrobiologyMedicine

Abstract

fetched live from OpenAlex

The antifungal activity of Aniba rosaeodora, Laurus nobilis, Sassafras albidum and Cinnamomum zeylanicum essential oils were investigated against 17 micromycetes. Among the tested fungal species were food poisoning, spoilage fungi, plant and animal pathogens. In order to determine fungistatic and fungicidal concentrations (MIC and MFC) macrodilution and microdilution tests were used. Linalool was the main component in the essential oil of A. rosaeodora, while 1.8-cineole was dominant in L. nobilis. In sassafras essential oil safrole was the major component and in the oil of C. zeylanicum the main component was trans-cinnamaldehyde. The essential oil of cinnamon showed the strongest antifungal activity.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.028
Threshold uncertainty score0.347

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.028
GPT teacher head0.291
Teacher spread0.263 · 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