MétaCan
Menu
Back to cohort
Record W4409360426 · doi:10.1139/cjps-2024-0185

Trends in production, consumption, trade, and research of dry beans across the globe and Canada

2025· article· en· W4409360426 on OpenAlexaffvenueabout
Mohsen Hesami, Mohsen Yoosefzadeh-Najafabadi

Bibliographic record

VenueCanadian Journal of Plant Science · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant pathogens and resistance mechanisms
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsProduction (economics)Consumption (sociology)GlobeDry beanBiologyAgronomyAgricultural economicsEnvironmental scienceEconomicsCultivar

Abstract

fetched live from OpenAlex

Dry beans ( Phaseolus vulgaris L.) are known as a significant component of global agri-food systems, in regions such as Southern Asia, Eastern Africa, and South America, where they also serve as a valuable source of feed. Over the past few decades, global production has grown significantly, driven by rising demand, technological advancements, improved yields, and expanded cultivation areas. Canada, in particular, has become a significant player in the dry bean industry, leveraging its rich agricultural landscape and advanced agricultural technologies. Canadian research initiatives, financially supported by both governmental and private funding, have concentrated on developing new bean varieties with higher yields, resistance to pests and diseases, better adaptation to local growing conditions, and improved nutritional profiles. This study reviews trends in dry bean production, consumption, and international trade over the past decades, emphasizing the implications for research on both global and Canadian scales. Collaborative efforts between Canadian institutions and international research organizations have facilitated the exchange of genetic resources and agronomic techniques, thereby enhancing productivity and sustainability. By investing in these innovative endeavors, Canada not only bolsters its strengthened agricultural sector but also contributes significantly to global food security and the achievement of sustainable development goals.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.177

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0090.026
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.033
GPT teacher head0.266
Teacher spread0.234 · 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 designObservational
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

Citations3
Published2025
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Plant ScienceSame topicPlant pathogens and resistance mechanismsFrench-language works237,207