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Record W3087486246 · doi:10.1002/ptr.6863

<i>Vicia plan</i>ts—A comprehensive review on chemical composition and phytopharmacology

2020· review· en· W3087486246 on OpenAlex
Bahare Salehi, Ibrahim M. Abu‐Reidah, Farukh Sharopov, Natallia Karazhan, Javad Sharifi‐Rad, Muhammad Akram, Fahad Said Khan, Wafa Abbaass, Rida Zainab, Katya Carbone, Nouran M. Fahmy, Eman Al‐Sayed, Mohamed El‐Shazly, Massimo Lucarini, Alessandra Durazzo, Antonello Santini, Miquel Martorell, Raffaele Pezzani

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 · 2020
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicGenetic and Environmental Crop Studies
Canadian institutionsGovernment of Newfoundland and LabradorMemorial University of Newfoundland
Fundersnot available
KeywordsComposition (language)Chemical compositionPlan (archaeology)ChemistryGeographyOrganic chemistryPhilosophyLinguisticsArchaeology

Abstract

fetched live from OpenAlex

The plants belonging to the genus Vicia are of great interest as a source of many bioactive compounds and micronutrients. A snapshot of their cultivation, habitat, main components, from which essential oils can be obtained, is given. The traditional medicinal uses of Vicia plants are also reported, as well as the wide spectrum of the main biological activities attributed to Vicia plants is discussed regarding potential health beneficial properties, in particular anti-Parkinson, anticholinesterase, antidepressant, anticonvulsant, antimicrobial, cytotoxic, antioxidant, antiinflammatory and antinociceptive, antidiabetic, antihemolytic, anticoagulant, estrogenic, diuretic, antihypoxic activities.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.985
Threshold uncertainty score0.502

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.211
GPT teacher head0.405
Teacher spread0.195 · 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