Prosecution Insights
Prosecution Insights
2 pending office actions • 0 art units • 2 examiners • 0 of 2 (0%) have an AI response strategy ready
Dongguan University Of Technology currently has 2 pending office actions. These actions are assigned to 2 distinct examiners, meaning each pending matter is being reviewed by a different individual. The data shows 0 distinct art units, indicating the filings are not currently categorized within specific administrative divisions.
OLSON, LARS A is the busiest examiner for this portfolio, holding 1 pending office action. Since OLSON, LARS A and the other distinct examiner each have 1 action, the workload is distributed across the entire examiner pool. Success in the 2 pending office actions will depend on addressing the specific requirements of both OLSON, LARS A and the other examiner.
Difficulty is derived from the rejection statutes on the most recent pending office action. §101-driven and multi-statute cases are graded Hard; §112-only and obviousness-type double-patenting cases are graded Easy; everything else is Medium. "Unknown" means we have not yet parsed a statute for that office action.
| Bucket | Cases |
|---|---|
| §101 only | 1 (50%) |
| Multi-statute (no §101) | 1 (50%) |
How the docket's pending cases split across USPTO tech-center bands.
Manual office-action response work runs about 10 hours per case. The time-saved bands below show what IP Author's prosecution pipeline typically delivers — a conservative 20% on the low end, 35% in the middle, 50% on the high end.
| Examiner | Apps on this docket | Allow rate | Interview lift |
|---|---|---|---|
| OLSON, LARS A | 1 | 81.9% | +14.0% |
| HONORE, EVEL NMN | 1 | 51.9% | +26.4% |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 2 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18894395 | BIONIC RESCUE ROBOT FISH | OLSON, LARS A | — |
| 18613118 | ATTRIBUTE INFERENCE METHOD FOR CO-TRAINING DATA, COMPUTING DEVICE, AND STORAGE MEDIUM THEREOF | HONORE, EVEL NMN | — |
Cases in front of an examiner whose interview lift is 10 percentage points or more — i.e. interviewed cases historically resolve more favorably than non-interviewed ones. The top 2 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18894395 | BIONIC RESCUE ROBOT FISH | OLSON, LARS A | — |
| 18613118 | ATTRIBUTE INFERENCE METHOD FOR CO-TRAINING DATA, COMPUTING DEVICE, AND STORAGE MEDIUM THEREOF | HONORE, EVEL NMN | — |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 18894395 | BIONIC RESCUE ROBOT FISH | OLSON, LARS A | — | §103§112 | Non-Final OA | — | Pending | Sep 24, 2024 |
| 18613118 | ATTRIBUTE INFERENCE METHOD FOR CO-TRAINING DATA, COMPUTING DEVICE, AND STORAGE MEDIUM THEREOF | HONORE, EVEL NMN | — | §101 | Non-Final OA | — | Pending | Mar 22, 2024 |
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