MétaCan
Menu
Back to cohort
Record W2186404447 · doi:10.1079/9781845932015.0161

The impact of intellectual property rights in the plant and seed industry.

2007· book-chapter· en· W2186404447 on OpenAlexaff
Tirtha Dhar, Jeremy D. Foltz

Bibliographic record

VenueCABI eBooks · 2007
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Property and Patents
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsIntellectual propertyBusinessLaw and economicsEconomicsPolitical scienceLaw

Abstract

fetched live from OpenAlex

This work uses changes in intellectual property rights regimes for plants as a way to identify the value and cost to industries and society of the different components of property rights: exclusivity, research exemptions, and revelation of research outcomes. A simple model is described that can account for these differences in company choice of intellectual property versus keeping trade secrets. The data used include observations on multiple crop types over a span of 20+ years across 3 different intellectual property rights regimes. Differences in the replicability of crop types are shown to cause intellectual property rights to have diverse sets of incentives for research and property rights claims.

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 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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.896
Threshold uncertainty score0.529

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.148
GPT teacher head0.244
Teacher spread0.096 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations10
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueCABI eBooksSame topicIntellectual Property and PatentsFrench-language works237,207