The Post-Grant Life: Coordinating & Strategizing Challenges of Issued Patents in Multiple Continents
Bibliographic record
Abstract
With the enactment of the Leahy-Smith American Invents Act (AIA), U.S. patent law gained a new post-grant opposition system and the Patent Trial and Appeal Board (PTAB). While the U.S. post-grant opposition system has some similarities to the post-grant systems, such as that in the European Union, Japan, South Korea, Canada, and Australia, there are also notable differences. Navigating one’s own post-grant system can be challenging, but doing so in multiple patent offices around the world is daunting. Differences in these proceedings not only present the potential for parties to make costly errors, but also to engage in strategic behavior. This Article discusses one such opportunity to engage in strategic behavior, one that is available due to a lack of international harmonization in the various post-grant systems around the world. In short, while the post-grant opposition system in the United States includes multiple estoppel statutes, there are no analogous estoppel statutes in many other post-grant systems, including that in the European Union and Japan. Because of this lack of harmonization, parties may test the strength of a competitor’s patent in multiple venues, as well as determine a competitor’s tolerance for financing simultaneous proceeding around the world.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.029 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.019 | 0.018 |
| Scholarly communication | 0.037 | 0.034 |
| Open science | 0.004 | 0.022 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".