What is the right approach of obviousness in patent litigation under Canada's pharmaceutical linkage relationships: To test or not to test?
Bibliographic record
Abstract
This thesis comprises an analysis of whether scientific research in the lead-up period to an invention by pharmaceutical companies should vitiate a finding of obviousness in patent litigation under Canada's linkage regulations ("Regulations"). Confusion over the test for obviousness was deemed to relate to a lack of understanding by courts of the inventive capacity of persons skilled in the art of pharmaceutical sciences. A purposive social sciences construction of the normative practices of such persons supports an approach to obviousness that would allow testing without vitiating a finding of obviousness. A suggestion toward a fair, unequivocal and predictable test is made which has its locus in Canadian law, federal policy underlying the Regulations and Supreme Court jurisprudence in leading patent cases. The proposed test is consistent with appellate court jurisprudence and commentary in other jurisdictions and provides a patent policy which facilitates rather than impedes innovation in the pharmaceutical sector.
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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 | 0.098 | 0.242 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.018 | 0.095 |
| Scholarly communication | 0.020 | 0.025 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.013 | 0.014 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".