Bibliographic record
Abstract
Abstract This chapter focuses on opposition proceedings. An opposition is to be contrasted with a re-examination in that in an opposition the validity of the application or patent is contested between the patentee and a third party, before the patent office, but without the patent office reviewing patentability in its own right. The timing of opposition proceedings varies between those jurisdictions which have them. Australian and German oppositions occur pre-grant, whereas those before the European Patent Office occur after grant. India has both pre- and post-grant opposition proceedings available. The patent offices which administer oppositions have also set out a range of procedural rules to govern the various steps which must be taken in ascertaining the grounds of opposition, preparation and filing of evidence, and so on. Opposition proceedings are not available in Canada, China, France, Italy, Japan, the Netherlands, or the United States. Nevertheless, legislation has been proposed in the United States to establish opposition procedures.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.097 | 0.030 |
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".