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PALYNOLOGICAL, PHYSICO-CHEMICAL AND BIOLOGICALLY ACTIVE SUBSTANCES PROFILE IN SOME TYPES OF HONEY IN THE REPUBLIC OF MOLDOVA

2021· article· en· W3199595738 on OpenAlexfundno aff
Aurica Chirsanova, Tatiana Capcanari, Alina Boiştean

Bibliographic record

VenueJournal of Engineering Science · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBee Products Chemical Analysis
Canadian institutionsnot available
FundersAgence Universitaire de la Francophonie
KeywordsRapeseedLavenderLavandulaBotanyPolyphenolBiologyOfficinalisHorticultureFood scienceTraditional medicineAntioxidantEssential oil

Abstract

fetched live from OpenAlex

Three types of monofloral honey (rapeseed honey, buckwheat and lavender) from the Republic of Moldova were analyzed. The results of the palynological analysis showed that the samples had a dominant type of pollen (at least 45%). In the case of lavender honey, the pollen of the plant Lavandula angustifolia is present in an average value of 74.83 ± 0.3; in rapeseed honey - Brassica napus and for buckwheat honey -Fagopyrum esculentum in average values as follows: 56.07 ± 0.3 and 68.08 ± 0.2% respectively. The study of the content of biologically active substances showed that buckwheat honey is the richest in polyphenols (9.00 ± 0.11 mg gallic acid / kg) and carotenoids (4.24 ± 0.57 mg βcarotE / kg), and maximum content of flavonoids is in rapeseed honey (4.52 ± 0.28 mg catechin / kg). Thus, the obtained results confirm that the honey from the Republic of Moldova falls within the limits recommended by the international regulation assuming adequate working conditions, handling, collection and storage of honey by beekeepers from the Republic of Moldova.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.013
GPT teacher head0.210
Teacher spread0.196 · 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

Citations5
Published2021
Admission routes1
Has abstractyes

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