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Record W3034433771 · doi:10.32473/edis-fe1027-2017

The U.S. Tomato Industry: An Overview of Production and Trade

2018· article· en· W3034433771 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEDIS · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and soil sciences
Canadian institutionsnot available
Fundersnot available
KeywordsEconomic shortageProduction (economics)Agricultural economicsCompetition (biology)Government (linguistics)EconomicsResource (disambiguation)Rest (music)AgribusinessBusinessEconomyAgricultureGeography

Abstract

fetched live from OpenAlex

Tomatoes are one of the world's most consumed vegetable crops. In the United States, domestic production meets about 40% of the total domestic demand for fresh-market tomatoes, with the rest of the demand met by imports, mostly from Mexico and Canada. Since 2000, however, fresh tomato production in the United States has exhibited a steady declining trend. One major reason is the increased competition from Mexico. This 4-page fact sheet written by Zhengfei guan, Trina Biswas, and Feng Wu and published by the UF/IFAS Food and Resource Economics Department argues for US government measures to help the domestic tomato industry resolve labor shortages and encourage research and development of labor-saving technologies such as mechanical harvesting to make the US tomato industry more competitive and sustainable. http://edis.ifas.ufl.edu/fe1027

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.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.813
Threshold uncertainty score0.135

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.077
GPT teacher head0.278
Teacher spread0.201 · 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

Quick stats

Citations59
Published2018
Admission routes1
Has abstractyes

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