Bibliographic record
Abstract
Abstract This chapter assesses re-examination, which involves another review of the patentability of the invention by the patent office. Re-examinations may occur before or after grant, and some jurisdictions such as Australia have both pre- and post-grant re-examinations. The grounds on which a re-examination may occur vary. In Australia, Canada, and the United States, they must be based on prior art and are therefore restricted to novelty and inventive step. The degree to which a third party may be involved in a re-examination also varies. In Australia and in the ex parte procedure in the United States, a party requesting re-examination of another’s patent plays no further part thereafter. This is the formal position in Canada but in practice further material may be filed. The United States also has an inter partes re-examination procedure in which the third party may participate. In Japan, there is no re-examination procedure, although the patentee may make an appeal for correction of a patent. There is no provision for re-examination in the European Patent Office, France, India, Italy, and the Netherlands.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.116 | 0.047 |
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".