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Record W4252149050 · doi:10.1300/j492v06n02_03

Contribution of Health Attributes, Research Investment, and Innovation to Developments in the Blueberry Industry

2007· article· en· W4252149050 on OpenAlex
Richard Carew, Wojciech J. Florkowski, Senhui He

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Fruit Science · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBerry genetics and cultivation research
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsDiversification (marketing strategy)CultivarInvestment (military)BusinessProduction (economics)Yield (engineering)Consumer demandAgricultural economicsMarketingHorticultureEconomicsPolitical scienceBiology

Abstract

fetched live from OpenAlex

Abstract This paper examines how the United States and Canadian highbush and lowbush blueberry industries have changed over the last two decades. Production increases have been driven by a combination of changing consumer preferences for healthy foods and the development of new cultivars that have opened new production regions, expanded fresh market opportunities, and created new food products. Canada has found it advantageous and economical to invest its research effort in the development of the lowbush blueberry, exploiting its health protective properties. The Unites States has concentrated its research effort on highbush cultivars to lengthen the harvest window and promote diversification opportunities in the Southern United States. Highbush production expansion in the Pacific Northwest has relied very little on new cultivar development and improvements in yield but more on increases in cultivated area.

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)0.014
metaresearch head score (Gemma)0.001
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 score0.728
Threshold uncertainty score0.483

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
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 head0.179
GPT teacher head0.432
Teacher spread0.253 · 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