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Record W7116709823 · doi:10.18372/2786-5495.1.20578

«ТРИ СЕСТРИ» У СУЧАСНОМУ ХАРЧУВАННІ ЛЮДИНИ ЯК ІННОВАЦІЙНА ІНТЕГРАЦІЯ ТРАДИЦІЇ, НАУКИ ТА БІЗНЕСУ

2025· article· en· W7116709823 on OpenAlexaff
Надія Адамчук-Чала, Надежда Єфимищ, Єлизавета Чала

Bibliographic record

VenueProblems of a systemic approach to the economy enterprises (National Aviation University, Ukraine, Kyiv) · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicIndigenous Knowledge Systems and Agriculture
Canadian institutionsMcGill University
Fundersnot available
KeywordsTraditional knowledgeIntercroppingIndigenousFood systemsFood securityAgriculture

Abstract

fetched live from OpenAlex

This paper explores the agroecological, cultural, nutritional, and business-related significance of the «Three Sisters» intercropping system - corn, beans, and squash-rooted in Native American agricultural traditions. By analyzing scientific studies and meta-analyses, the authors assess how this system enhances land-use efficiency, soil health, pest resistance, and dietary quality. The study highlights the potential of combining traditional knowledge with modern science and entrepreneurial strategies to advance sustainable food systems, support Indigenous food sovereignty, and create business opportunities in local and global agri-food markets. It also addresses challenges such as reconciling cultural and scientific paradigms and land accessibility.

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)0.000
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: Empirical · Consensus signal: none
Teacher disagreement score0.732
Threshold uncertainty score0.703

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.009
GPT teacher head0.179
Teacher spread0.170 · 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 designNot applicable
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
Published2025
Admission routes1
Has abstractyes

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