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Record W2802831895 · doi:10.1002/ptr.6101

<i>Echinacea</i>plants as antioxidant and antibacterial agents: From traditional medicine to biotechnological applications

2018· review· en· W2802831895 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePhytotherapy Research · 2018
Typereview
Languageen
FieldMedicine
TopicHerbal Medicine Research Studies
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsEchinacea (animal)Traditional medicineContext (archaeology)AntimicrobialBiologyMedicinal plantsMedicineMicrobiology

Abstract

fetched live from OpenAlex

The genus Echinacea consists of 11 taxa of herbaceous and perennial flowering plants. In particular, Echinacea purpurea (L.) Moench is widely cultivated all over the United States, Canada, and in Europe, exclusively in Germany, for its beauty and reported medicinal properties. Echinacea extracts have been used traditionally as wound healing to improve the immune system and to treat respiratory symptoms caused by bacterial infections. Echinacea extracts have demonstrated antioxidant and antimicrobial activities, and to be safe. This survey aims at reviewing the medicinal properties of Echinacea species, their cultivation, chemical composition, and the potential uses of these plants as antioxidant and antibacterial agents in foods and in a clinical context. Moreover, the factors affecting the chemical composition of Echinacea spp. are also covered.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.922
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.002
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.362
GPT teacher head0.520
Teacher spread0.158 · 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