UK claim construction: return of the Protocol questions and file wrapper estoppel
Bibliographic record
Abstract
The law of patent construction in the UK has been largely settled since the 2004 House of Lords' decision in Kirin-Amgen which, in confirming purposive construction as the correct approach, ruled out any US-style doctrine of equivalence. It also doubted the utility of the Protocol Questions, despite their regular application by the UK courts and the adoption of similar questions in other EU jurisdictions. The law on file wrapper estoppel, the use of a patent's prosecution history to estop the patentee from arguing a different construction during litigation, has been settled for even longer. The UK courts have felt strongly that it should not be necessary to read the prosecution history in order to determine a patent's scope. Germany and Canada concur with the UK's approach, however, the US courts take the opposite stance with file wrapper estoppel providing a counterbalance to its doctrine of equivalents. Mr Justice Arnold's judgment in Actavis v Eli Lilly has reopened both these issues. Arnold J not only applied the previously defunct Protocol Questions in construing Eli Lilly's Alimta patent but then used the patent's prosecution history in deciding that its claim did not extend to cover Actavis's variant. This comes close to the US approach criticized by Lord Hoffmann in Kirin-Amgen and may lead to a resurrection of the Protocol Questions as a doctrine of equivalence, even if not explicitly recognized as such.
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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 | 0.101 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.013 |
| Scholarly communication | 0.018 | 0.017 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.022 | 0.015 |
| Insufficient payload (model declined to judge) | 0.020 | 0.007 |
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".