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Record W3127542320 · doi:10.33938/2011-150

CANADA'S FOREIGN TRADE IN AGRICULTURAL PRODUCTS: STATE PROGRAMS, STRUCTURE, DIRECTIONS

2020· article· en· W3127542320 on OpenAlexaboutno aff
Alevtina Getman

Bibliographic record

VenueEconomy labor management in agriculture · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsnot available
Fundersnot available
KeywordsAgricultureState (computer science)BusinessInternational tradeAgricultural economicsRegional scienceEconomicsGeographyComputer scienceArchaeologyProgramming language

Abstract

fetched live from OpenAlex

Изучение опыта развитых стран по организации экспорта продукции АПК и освоению новых рынков особенно актуально в настоящее время в свете задачи по масштабному увеличению агропродовольственного экспорта России. Канада хорошо известна в качестве одного из крупнейших экспортеров продукции АПК и ее опыт в этой области может быть использован агробизнесом России, положения закона о программах торговли агропродовольствием и программ господдержки сельского хозяйства и экспорта Канады – специалистами правительственных органов. Успех Канады в работе на мировых рынках агропродовольственной продукции в значительной степени определяется созданной в стране уникальной системой интегрированных усилий производителей, рыночных агентов и государства по продвижению продукции АПК на мировые рынки. Структуру системы образуют 44 специальные программы, направленные на развитие сельскохозяйственного производства и экспорта продукции АПК. Анализ структуры и географии канадского экспорта имеет своей целью исследование работы канадского аграрного бизнеса в регионах логистически привлекательных для российского экспорта агропродовольствия.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.055
Threshold uncertainty score0.399

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0040.002
Scholarly communication0.0050.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.000

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 head0.011
GPT teacher head0.185
Teacher spread0.174 · 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 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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