MétaCan
Menu
Back to cohort
Record W2791270191

Two Wrongs Don't Make a Patent Right

2005· article· en· W2791270191 on OpenAlexaboutno aff
David Catechi

Bibliographic record

VenueHastings law journal · 2005
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Property and Patents
Canadian institutionsnot available
Fundersnot available
KeywordsLaw and economicsBusinessComputer scienceSociology
DOInot available

Abstract

fetched live from OpenAlex

Recent litigation over genetically modified corn reveals an increasing imbalance between the property rights of genetic seed manufacturers and the rights of individual farmers. Common-law property doctrines and traditional patent law fail to protect farmers leaving them exposed to both potential genetic contamination of their crops and costly patent infringement liability. This Note proposes a simple yet effective solution-Notice. Requiring patent holders to provide notice to alleged infringing farmers sufficient to enable the farmer to cease infringement balances the rights of both the patent holder and the farmer. Litigation in both the United States and Canada regarding gentically modified corn stands boldly as an example for the problems and failed solutions in this arena. This proposal, however, can be applied broadly to any patent which can duplicate through self-replication. Finally, this Note suggests that because this solution lies within the Patent Act and not through the creation of additional equitable doctrines it is likely to be supported by the Federal Circuit.

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)0.013
metaresearch head score (Gemma)0.045
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.045
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0080.023
Scholarly communication0.0110.019
Open science0.0020.005
Research integrity0.0200.013
Insufficient payload (model declined to judge)0.0160.004

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 head0.100
GPT teacher head0.224
Teacher spread0.123 · 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 designTheoretical or conceptual
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

Citations0
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueHastings law journalSame topicIntellectual Property and PatentsFrench-language works237,207