<i>Sanofi-Aventis et al. v. Apotex Inc. et al.</i> : The one hundred eight million dollar question
Bibliographic record
Abstract
In Sanofi-Aventis et al. v. Apotex, Inc. et al., 659 F.3d 1171 (Fed. Cir. 2011), the Federal Circuit reversed a lower court's grant of prejudgment interest to Sanofi in view of a settlement agreement between the parties, affirmed the lower court's determination that Canadian-based Apotex Inc. was jointly and severally liable with American-based Apotex Corp. for all damages and denied a motion of Apotex Inc. and Apotex Corp. for leave to amend to add an affirmative defense of patent misuse and a counterclaim for breach of contract. Regarding the denial of prejudgment interest in the amount of $107,930,857, the Federal Circuit found that the term “actual damages” in the settlement agreement included all the damages to which Sanofi was entitled. This decision, accordingly, highlights the importance of drafting carefully crafted settlement agreements.
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 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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.034 | 0.014 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".