Secret Use before Priority Date
Bibliographic record
Abstract
Abstract This chapter examines the laws governing secret use before the priority date across major jurisdictions, highlighting its impact on patent validity. In Australia, secret use triggers revocation if it confers commercial benefit and extends the effective patent term. Canada requires absolute novelty but allows a one-year grace period for inventor-derived disclosure, and secret prior use grants limited rights without invalidating patents. China demands absolute novelty, excluding secret technical disclosures from prior art unless breach of secrecy makes them public, while India treats secret use as a ground for revocation unless it occurs under government authorisation, reasonable trial, or without consent. Japan grants a non-exclusive licence for secret prior users meeting specific conditions, whereas in the United States, secret use by inventors can bar patentability under commercial exploitation rules, while third-party secret use generally does not. Finally, the chapter outlines Europe’s approach, where public use defeats novelty but secret prior use may grant defensive rights, particularly under national laws in France, Germany, Italy, the Netherlands, and the United Kingdom.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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; both teacher heads agree on what is shown here.
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".