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Record W2398783952

The Duty to Disclose 'The Invention': The Wrong Tool for the Job

2013· article· en· W2398783952 on OpenAlexaffabout
Norman Siebrasse

Bibliographic record

VenueSSRN Electronic Journal · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Property and Patents
Canadian institutionsUniversity of New BrunswickUniversity of Fredericton
Fundersnot available
KeywordsDutySupreme courtInventionLaw and economicsLawPatent trollReading (process)Good faithFaithPatent lawBusinessPolitical scienceIntellectual propertyEconomicsPhilosophyEpistemology
DOInot available

Abstract

fetched live from OpenAlex

In its Sildenafil decision, the Supreme Court of Canada held Pfizer’s Viagra patent to be invalid for failure to disclose “the invention,” though it provided no explicit definition of that term. I argue that on the best reading of the decision, “the invention” means the new, useful, non-obvious contribution to knowledge which is disclosed in the patent. While this is initially attractive, I argue that on this definition, a duty to disclose the invention is unsound as a matter of law and policy, because it implies that if any important claim in a patent is invalid, all the claims will be invalid. This eviscerates Section 58 of the Patent Act, which provides that claims stand or fall independently. I argue that the Court’s reasoning was motivated by a mistaken belief that at the time of the application Pfizer had tested the other claimed compounds and knew them to be ineffective in treating ED, and that it claimed those compounds primarily to conceal the true invention. I argue that even if the Court’s understanding of the facts was correct, a duty to disclose the invention is not the appropriate tool to address the issue. The case properly raises questions relating to the duty of good faith disclosure, not a duty to disclose the invention.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.389
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.046
GPT teacher head0.222
Teacher spread0.176 · 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.

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
Published2013
Admission routes2
Has abstractyes

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