What Amendments are Allowable?
Bibliographic record
Abstract
Abstract This chapter discusses what amendments to patents are allowable in Australia, Canada, China, India, Japan, the United States, France, Germany, Italy, the Netherlands, and the United Kingdom. In general, whether an amendment will be allowed depends on the effect that it will have on the monopoly conferred by the patent and the extent to which it is supported by the specification as filed. Amendments which go beyond the disclosure in the specification as filed and/or act to broaden the scope of the monopoly are not allowed. However, amendments may be more readily made, even if they broaden the scope of the claims, if it can be established that they correct a trivial mistake, such as a clerical error. The scope of allowable amendments tends to vary with the stage of the patent application or patent. This is because one of the hallmarks of the patent system is to provide certainty to the general public as to the scope of patent rights to be avoided. In Canada and the United States, patent claims may only be broadened by amendment where the conditions required for reissue applications are met.
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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.015 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".