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Record W4245244095 · doi:10.1504/ijtgm.2017.090279

US mushroom import demand estimation with the source-differentiated AIDS model

2017· article· en· W4245244095 on OpenAlexaboutno aff
Jun Li, Azzeddine Azzam

Bibliographic record

VenueInternational Journal of Trade and Global Markets · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicWine Industry and Tourism
Canadian institutionsnot available
Fundersnot available
KeywordsMushroomAlmost ideal demand systemRevenueChinaEconomicsConsumption (sociology)Consumer demandAgricultural economicsMarket shareBusinessEstimationProduction (economics)Market economyMicroeconomicsMarketingFood scienceBiology

Abstract

fetched live from OpenAlex

Recognising that the share of imports in total consumption has been increasing, and will likely continue to do so as US consumers adopt healthier diets, the goal of this paper is to contribute to the understanding of US mushroom demand by estimating the first-ever import demand elasticities for canned and fresh mushrooms by source. Price elasticities from a source-differentiated almost ideal demand system (AIDS) model suggest that while Canada, the leading exporter of fresh mushrooms to the US, may gain more revenue from rising mushroom prices; China, the leading exporter of canned mushrooms to the US may lose. The expenditure elasticities suggest that Chinese exporters of canned mushrooms stand to gain more from rising US spending on imported mushrooms than Canadian exporters of fresh mushrooms. Should NAFTA be scrapped and tariffs imposed, Mexico will lose more market share in the US fresh mushroom market than Canada.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.243
Teacher spread0.230 · 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 designSimulation or modeling
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
Published2017
Admission routes1
Has abstractyes

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