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Record W2034860154 · doi:10.1080/15538360902801338

Developments in Raspberry Production, Cultivar Releases, and Intellectual Property Rights: A Comparative Study of British Columbia and Washington State

2009· article· en· W2034860154 on OpenAlexaffabout
Richard Carew, Chaim Kempler, Patrick P. Moore, Tom Walters

Bibliographic record

VenueInternational Journal of Fruit Science · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBerry genetics and cultivation research
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsCultivarIntellectual propertyBlowing a raspberryGermplasmProduction (economics)BusinessAgroforestryBiologyPolitical scienceAgronomyHorticultureEconomicsLaw

Abstract

fetched live from OpenAlex

The Pacific Northwest (PNW) raspberry industry has undergone substantial structural changes over the last two decades driven by shifts in production and trade and strengthened intellectual property rights to protect cultivars. Since the mid-1980's, Washington raspberry production has increased substantively while British Columbia (BC) production has exhibited a downward decline. Plant breeding in the PNW has been affected by the increased globalization of the raspberry trade and the increased emphasis on plant patents and plant breeder's rights to protect cultivars. The increased emphasis on intellectual property rights to protect cultivars is likely to affect the accessibility of germplasm and the transaction costs of procuring planting material from European breeding programs. Raspberry research in BC has concentrated its efforts in developing improved cultivars with little research on the effects of management practices on fruit yields. The development of improved cultivars in the PNW has relied on conventional or classical breeding approaches. With reduced public support for raspberry breeding research in the PNW, breeding programs rely more heavily on support from industry associations. Future prosperity of the PNW raspberry industry would require developing competitive cultivars and promoting intellectual property protection to stimulate market development and the world-wide dissemination of improved cultivars.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.034
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.008
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.036
GPT teacher head0.289
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

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

Citations6
Published2009
Admission routes2
Has abstractyes

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