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Record W4400525637 · doi:10.47552/ijam.v15i2.4616

Apis mellifera honey: Healing effects - A value chain view from mountain agriculture

2024· article· en· W4400525637 on OpenAlexaff
Mihai Covaci, Brîndușa Covaci, Carla Selma

Bibliographic record

VenueInternational Journal of Ayurvedic Medicine · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBee Products Chemical Analysis
Canadian institutionsHyperion Technologies (Canada)
Fundersnot available
KeywordsBeekeepingAgricultureHoney beeProduction (economics)Value chainGeographyValue (mathematics)AgroforestryBiologyEcologyAgricultural scienceSupply chainBusinessMarketingEconomicsMathematicsStatistics

Abstract

fetched live from OpenAlex

Aims and objectives: This study systematically investigates Apis Mellifera honey as an integral component within the beekeeping value chain, specifically emphasizing its role in apicultural mountain production. Methods: The research delves into multifaceted dimensions, encompassing agronomical and territorial profiles, generated through the utilization of the Paintmap online software. Additionally, the investigation employs experimental and statistical perspectives, utilizing SPSS and Excel software for analysis. Important observations and results: The outcomes of this comprehensive analysis reveal a noteworthy evolution in the Apis Mellifera honey market, particularly during the prevailing pandemic circumstances. The findings elucidate a discernible surge in market development over recent years. Ultimately, the paper posits that the value chain associated with Apis Mellifera mountain honey originating from European Romania substantiates a substantial foundation for mountain production and agricultural practices. In summation, this exploration contributes to the scholarly understanding of the intricate dynamics within the apicultural sector, shedding light on the pivotal role of Apis Mellifera honey in sustaining robust mountain production and farming 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.

How this classification was reachedexpand

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.554
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.012
GPT teacher head0.253
Teacher spread0.241 · 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 teacher head, 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

Citations0
Published2024
Admission routes1
Has abstractyes

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