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Record W1976709741 · doi:10.1350/enlr.2005.7.4.278

Patent Liability and Genetic Drift

2005· article· en· W1976709741 on OpenAlexaboutno aff
Robert Burrell, Stephen Hubicki

Bibliographic record

VenueEnvironmental Law Review · 2005
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Property and Patents
Canadian institutionsnot available
Fundersnot available
KeywordsAppealSupreme courtPatent infringementLiabilityLawVictoryScope (computer science)BusinessLaw and economicsPolitical scienceEconomicsIntellectual propertyPolitics

Abstract

fetched live from OpenAlex

The Canadian case Monsanto v Schmeiser has attracted considerable attention around the world. The Schmeiser litigation has, in particular, raised fears about the scope of patent liability in cases of genetic drift. Patent infringement is not dependent upon proof of knowledge on the part of the defendant. There is therefore the possibility that farmers who, through no fault of their own, end up with patented varieties of genetically-modified (GM) plants or animals on their land will be held liable for patent infringement in certain circumstances. Schmeiser has come to be representative of these concerns, because although it was held that the defendant was aware of the presence of the GM variety, at neither first instance nor on appeal to the Federal Court of Appeal was this finding treated as directly relevant to the question of infringement. In contrast, in its decision the Supreme Court of Canada showed greater awareness of the problem of innocent infringement. Most significantly, the majority construed elements of the test for patent infringement in such a way as to make it less likely that an entirely innocent defendant would be held to infringe. Unfortunately, however, the Court’s approach also leaves a number of important questions unanswered and it is unclear what impact the decision will have in other jurisdictions. A further complicating factor is that although the defendant was found to have infringed, Monsanto was not awarded a financial remedy and had to pay its own costs. This has led some commentators to present the decision as a pyrrhic victory for Monsanto. This interpretation should be treated with caution, however, since it may distract attention from Schmeiser’s potential significance.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.968
Threshold uncertainty score0.997

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)0.0040.004

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 head0.075
GPT teacher head0.200
Teacher spread0.125 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations3
Published2005
Admission routes1
Has abstractyes

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