Detailed information about the 100 most recent patent applications.
| Application Number | Title | Filing Date | Disposal Date | Disposition | Time (months) | Office Actions | Restrictions | Interview | Appeal |
|---|---|---|---|---|---|---|---|---|---|
| 17139674 | SYSTEMS AND METHODS FOR PROVIDING A UNIVERSAL OCCUPATIONAL TAXONOMY | December 2020 | April 2024 | Allow | 39 | 2 | 0 | Yes | No |
| 17139199 | SYSTEMS AND METHODS FOR DETERMINING PROFITABILITY SCORE OF AN INCOMING CUSTOMER CALL | December 2020 | April 2024 | Abandon | 40 | 3 | 0 | No | No |
| 17104746 | METHODS AND SYSTEMS FOR ORDERING EXPEDITED PRODUCTION OR SUPPLY OF DESIGNED PRODUCTS | November 2020 | June 2022 | Allow | 18 | 3 | 0 | Yes | No |
| 16950544 | SMART ORCHARD HARVESTING CART WITH ANALYTICS | November 2020 | June 2025 | Abandon | 55 | 4 | 0 | No | Yes |
| 17081321 | TRANSPORTATION PLAN GENERATION APPARATUS AND TRANSPORTATION PLAN GENERATION METHOD | October 2020 | September 2022 | Abandon | 23 | 2 | 0 | Yes | No |
| 17029423 | HIT OR MISS INSIGHT ANALYSIS | September 2020 | September 2024 | Abandon | 48 | 5 | 0 | Yes | No |
| 17027136 | METHODS AND SYSTEMS FOR PREDICTING WAIT TIME OF QUEUES AT SERVICE AREA | September 2020 | February 2023 | Allow | 29 | 2 | 0 | No | No |
| 16982320 | AUGMENTED MANAGEMENT SYSTEM AND METHOD | September 2020 | January 2023 | Abandon | 28 | 2 | 0 | No | No |
| 17018426 | COGNITIVE ASSESSMENT OF DIGITAL CONTENT | September 2020 | June 2025 | Abandon | 57 | 7 | 0 | Yes | No |
| 17010513 | DETECTION OF EVASIVE ITEM LISTINGS | September 2020 | June 2023 | Allow | 34 | 3 | 0 | Yes | No |
| 17003463 | UTILIZING MACHINE LEARNING MODELS TO AGGREGATE APPLICATIONS AND USERS WITH EVENTS ASSOCIATED WITH THE APPLICATIONS | August 2020 | October 2022 | Allow | 26 | 1 | 0 | Yes | No |
| 16995114 | SYSTEM, METHOD, AND COMPUTER-ACCESSIBLE MEDIUM FOR DETECTING AND REMEDIATING IN-PERSON CART ABANDONMENT | August 2020 | July 2024 | Allow | 47 | 4 | 0 | Yes | No |
| 16942355 | MULTI-FACETED LARGE-SCALE FORECASTING | July 2020 | July 2022 | Abandon | 24 | 2 | 0 | No | No |
| 16942226 | SUBSCRIPTION RENEWAL PREDICTION WITH A COOPERATIVE COMPONENT | July 2020 | February 2023 | Abandon | 31 | 2 | 0 | No | No |
| 16930279 | SELF-SUPERVISED SYSTEM GENERATING EMBEDDINGS REPRESENTING SEQUENCED ACTIVITY | July 2020 | March 2024 | Allow | 44 | 4 | 0 | Yes | No |
| 16928897 | DETERMINING AND APPLYING ATTRIBUTE DEFINITIONS TO DIGITAL SURVEY DATA TO GENERATE SURVEY ANALYSES | July 2020 | June 2024 | Allow | 47 | 5 | 0 | Yes | No |
| 16925199 | MACHINE LEARNING SYSTEM, METHOD, AND COMPUTER PROGRAM FOR HOUSEHOLD MARKETING SEGMENTATION | July 2020 | February 2023 | Allow | 32 | 2 | 0 | No | No |
| 16916930 | CONTEXTUAL MARKETING SYSTEM BASED ON PREDICTIVE MODELING OF USERS OF A SYSTEM AND/OR SERVICE | June 2020 | January 2023 | Allow | 31 | 2 | 0 | Yes | No |
| 16897316 | Method for Generating User Feedback Information From a Product Use Event and User Profile Data to Enhance Product Use Results | June 2020 | November 2022 | Abandon | 30 | 2 | 0 | No | No |
| 16883316 | AUTOMATIC MOVIE PERFORMANCE PREDICTOR | May 2020 | May 2023 | Allow | 36 | 2 | 0 | Yes | No |
| 16862088 | ARTIFICIAL INTELLIGENCE-DRIVEN METHOD AND SYSTEM FOR SIMPLIFIED SOFTWARE DEPLOYMENTS | April 2020 | April 2025 | Abandon | 60 | 6 | 0 | No | No |
| 16851759 | METHOD AND APPARATUS FOR OPTIMIZING OBJECT PREDICTION AND STORAGE MEDIUM | April 2020 | February 2024 | Abandon | 46 | 4 | 0 | No | No |
| 16756972 | INFORMATION PROCESSING APPARATUS, RISK FORECASTING METHOD, AND PROGRAM | April 2020 | November 2022 | Abandon | 31 | 1 | 0 | No | No |
| 16843382 | SYSTEM AND METHOD FOR MODEL BASED PRODUCT DEVELOPMENT FORECASTING | April 2020 | December 2023 | Abandon | 44 | 4 | 0 | No | No |
| 16821329 | SYSTEMS AND METHODS TO RECOMMEND PRICE OF BENEFIT ITEMS OFFERED THROUGH A MEMBERSHIP PLATFORM | March 2020 | March 2022 | Allow | 24 | 1 | 0 | Yes | No |
| 16817936 | CONSTRAINT PLANNER ENGINE | March 2020 | April 2024 | Abandon | 49 | 4 | 0 | No | No |
| 16818586 | TIME SERIES CLUSTERING ANALYSIS FOR FORECASTING DEMAND | March 2020 | March 2023 | Allow | 36 | 2 | 0 | Yes | No |
| 16645228 | MAINTENANCE RANGE OPTIMIZATION APPARATUS, MAINTENANCE RANGE OPTIMIZATION METHOD, AND COMPUTER-READABLE RECORDING MEDIUM | March 2020 | June 2022 | Allow | 27 | 2 | 0 | Yes | No |
| 16809198 | MODIFYING DATA CLEANSING TECHNIQUES FOR TRAINING AND VALIDATING AN ARTIFICIAL NEURAL NETWORK MODEL | March 2020 | August 2023 | Allow | 42 | 2 | 0 | No | No |
| 16776459 | System and Method for Generating Networking Referrals | January 2020 | February 2022 | Abandon | 24 | 1 | 0 | No | No |
| 16634577 | ESTIMATING SYSTEM, ESTIMATING METHOD AND PROGRAM | January 2020 | April 2025 | Abandon | 60 | 6 | 0 | Yes | No |
| 16774223 | ADAPTIVE GROUPING OF WORK ITEMS | January 2020 | August 2023 | Abandon | 43 | 5 | 0 | Yes | No |
| 16748100 | BUILDING TIME SERIES BASED PREDICTION / FORECAST MODEL FOR A TELECOMMUNICATION NETWORK | January 2020 | October 2023 | Allow | 45 | 3 | 0 | Yes | No |
| 16632510 | MACHINE LEARNING AND OBJECT SEARCHING METHOD AND DEVICE | January 2020 | October 2022 | Allow | 33 | 1 | 0 | No | No |
| 16743486 | DEEP REINFORCEMENT LEARNING FOR LONG TERM REWARDS IN AN ONLINE CONNECTION NETWORK | January 2020 | December 2022 | Allow | 35 | 2 | 0 | Yes | No |
| 16739801 | ARTIFICIAL INTELLIGENCE SYSTEMS AND METHODS CONFIGURED TO PREDICT TEAM MANAGEMENT DECISIONS | January 2020 | October 2022 | Allow | 33 | 2 | 0 | Yes | No |
| 16736684 | Assessing Impact of Media Data Upon Brand Worth | January 2020 | June 2023 | Abandon | 42 | 4 | 0 | Yes | No |
| 16713066 | PROGRESS RATE ROLL-UP SYSTEM FROM LOWER LEVEL TO UPPER LEVEL FOR ENGINEERING CONTROL SYSTEM OF POWER PLANT CONSTRUCTION PROJECT | December 2019 | December 2021 | Abandon | 25 | 1 | 0 | No | No |
| 16714297 | DISPLAY OF MULTI-MODAL VEHICLE INDICATORS ON A MAP | December 2019 | February 2025 | Allow | 60 | 4 | 0 | Yes | No |
| 16700760 | SYSTEM AND METHOD FOR PRODUCT DEMAND TRANSFER ESTIMATION THROUGH MACHINE LEARNING | December 2019 | April 2023 | Allow | 40 | 3 | 0 | No | No |
| 16700813 | Using Machine Learning to Train and Generate an Insight Engine for Determining a Predicted Sales Insight | December 2019 | October 2022 | Allow | 35 | 2 | 0 | Yes | No |
| 16697665 | DYNAMIC SELECTABLE AUXILIARY RESOURCE PLATFORM | November 2019 | November 2023 | Abandon | 47 | 4 | 0 | No | No |
| 16697869 | MACHINE LEARNING-BASED PRODUCT AND SERVICE DESIGN GENERATOR | November 2019 | July 2024 | Abandon | 55 | 6 | 0 | No | No |
| 16695579 | SYSTEM AND A METHOD FOR OPTIMIZING SOLUTION IDENTIFICATION FOR A PROBLEM | November 2019 | December 2021 | Abandon | 24 | 1 | 0 | No | No |
| 16689311 | System and Method for Improving Sales Force Performance | November 2019 | June 2022 | Abandon | 30 | 2 | 0 | No | No |
| 16685549 | DYNAMIC FOOD PRICING ENGINE | November 2019 | January 2025 | Abandon | 60 | 6 | 0 | Yes | No |
| 16675313 | COLLABORATIVE DEVELOPMENT | November 2019 | November 2023 | Allow | 49 | 4 | 0 | No | No |
| 16610979 | INFORMATION PROCESSING SYSTEM, INFORMATION PROCESSING DEVICE, PREDICTION MODEL EXTRACTION METHOD, AND PREDICTION MODEL EXTRACTION PROGRAM | November 2019 | December 2021 | Abandon | 25 | 1 | 0 | No | No |
| 16674472 | INTELLIGENT AGENT TO SIMULATE CUSTOMER DATA | November 2019 | September 2023 | Allow | 46 | 4 | 0 | Yes | No |
| 16673374 | RESOURCE ALLOCATION USING SCALABLE NON-MYOPIC ATOMIC GAME FOR SMART PARKING AND OTHER APPLICATIONS | November 2019 | October 2021 | Allow | 23 | 1 | 0 | Yes | No |
| 16498508 | Method and System for Managing and/or Monitoring a Project or a Process | October 2019 | July 2024 | Abandon | 57 | 2 | 0 | No | Yes |
| 16664433 | System and Method for Generating Predictive Insights Using Self-Adaptive Learning | October 2019 | October 2021 | Abandon | 24 | 1 | 0 | No | No |
| 16599505 | GENERATING MODE CHANGE ALERTS WITH AUTOMATIC DETECTION FROM SENSOR DATA | October 2019 | May 2022 | Allow | 31 | 3 | 0 | Yes | No |
| 16593924 | Computer System and Method for Facilitating Creation and Management of an Inspection and Test Plan for a Construction Project | October 2019 | December 2024 | Abandon | 60 | 5 | 0 | Yes | Yes |
| 16578836 | OPTIMIZED BATCHED POLYTOPE PROJECTION | September 2019 | September 2022 | Allow | 36 | 4 | 0 | Yes | No |
| 16578719 | METHOD, APPARATUS, AND COMPUTER-READABLE MEDIUM FOR DETERMINING CUSTOMER ADOPTION BASED ON MONITORED DATA | September 2019 | November 2021 | Abandon | 26 | 2 | 0 | Yes | Yes |
| 16489923 | INFORMATION PROCESSING DEVICE, TERMINAL DEVICE, INFORMATION PROCESSING METHOD, AND RECORDING MEDIUM | August 2019 | February 2022 | Allow | 29 | 2 | 0 | No | No |
| 16544275 | TECHNIQUES FOR DETECTING WHEN INVITEES ARE PRESENT OR REMOTE | August 2019 | August 2022 | Abandon | 36 | 4 | 0 | No | No |
| 16486487 | GOOD TIME TO CALL | August 2019 | June 2021 | Abandon | 22 | 1 | 0 | No | No |
| 16531177 | METHODS AND SYSTEMS FOR WORKPLACE RISK ASSESSMENT | August 2019 | November 2022 | Allow | 39 | 5 | 0 | Yes | No |
| 16423649 | DYNAMIC ORDERING OF TASKS IN A TASK SATURATED TIMELINE | May 2019 | January 2025 | Abandon | 60 | 4 | 0 | Yes | Yes |
| 16388585 | FACILITATING FIELD DATA COLLECTION USING HIERARCHICAL SURVEYS | April 2019 | August 2020 | Abandon | 16 | 1 | 0 | No | No |
| 16295118 | FACILITATING POSITIVE RESPONSES FOR ELECTRONIC COMMUNICATIONS FROM TEMPORAL GROUPS | March 2019 | January 2023 | Abandon | 46 | 4 | 0 | Yes | No |
| 16261852 | PREDICTING A WORK PROGRESS METRIC FOR A USER | January 2019 | March 2025 | Abandon | 60 | 10 | 0 | Yes | No |
| 16217918 | GROUPING ASSOCIATED CUSTOMERS WITH A CONNECTED CUSTOMER | December 2018 | January 2023 | Abandon | 49 | 6 | 0 | No | No |
| 15987502 | ADAPTIVE PRIOR SELECTION IN ONLINE EXPERIMENTS | May 2018 | September 2021 | Abandon | 39 | 1 | 0 | No | No |
| 15747469 | INFORMATION PROCESSING SYSTEM AND INFORMATION PROCESSING METHOD | January 2018 | August 2021 | Allow | 42 | 2 | 0 | No | No |
| 15880425 | OPERATIONAL METRICS FOR ELECTRONIC DEVICES | January 2018 | March 2022 | Abandon | 50 | 3 | 0 | Yes | No |
| 15880524 | LOCATION-AWARE DEVICE TRACKING SYSTEM | January 2018 | May 2021 | Abandon | 40 | 1 | 0 | No | No |
| 15879022 | System and Method for Identifying and Assigning Professionals for a Particular Task | January 2018 | March 2021 | Abandon | 38 | 1 | 0 | No | No |
| 15878955 | MANAGING ACTIVITIES ON INDUSTRIAL PRODUCTS ACCORDING TO COMPLIANCE WITH REFERENCE POLICIES | January 2018 | September 2021 | Allow | 44 | 3 | 0 | Yes | No |
| 15843035 | COGNITIVE MANAGEMENT OF MULTIPLE SUBACCOUNTS | December 2017 | September 2022 | Allow | 57 | 4 | 0 | Yes | No |
| 15815456 | SKILL-SPECIFIC CONTRIBUTOR RATING SYSTEM | November 2017 | December 2022 | Abandon | 60 | 3 | 0 | Yes | No |
| 15574317 | BUSINESS OPERATIONS ASSISTANCE DEVICE AND BUSINESS OPERATIONS ASSISTANCE METHOD USING CONTRACT CANCELLATION PREDICTION | November 2017 | September 2022 | Abandon | 58 | 6 | 0 | Yes | No |
| 15813922 | SYSTEM AND METHOD FOR EVENT MANAGEMENT IN AN ONLINE VIRTUAL LEARNING ENVIRONMENT WITH INTEGRATED REAL-LEARNING AUGMENTATION AND CYBER WORKFORCE OPTIMIZATION | November 2017 | December 2020 | Abandon | 37 | 1 | 0 | No | No |
| 15573989 | PERSONAL BEHAVIOR ANALYSIS DEVICE, PERSONAL BEHAVIOR ANALYSIS SYSTEM, AND PERSONAL BEHAVIOR ANALYSIS METHOD | November 2017 | December 2020 | Abandon | 37 | 2 | 0 | No | No |
| 15812739 | SOCIAL MEDIA NETWORK MINING | November 2017 | April 2022 | Abandon | 53 | 4 | 0 | Yes | No |
| 15812295 | COMPOSITE ACCOUNT STRUCTURE | November 2017 | January 2021 | Abandon | 38 | 2 | 0 | Yes | No |
| 15534733 | EVALUATING PERFORMANCE OF APPLICATIONS UTILIZING USER EMOTIONAL STATE PENALTIES | June 2017 | December 2020 | Abandon | 43 | 4 | 0 | Yes | No |
| 15617447 | DATA COLLECTION AND CORRELATION | June 2017 | July 2020 | Abandon | 37 | 2 | 0 | Yes | No |
| 15617179 | WORK PLAN SUPPORT INFORMATION PROVISION METHOD, WORK PLAN SUPPORT INFORMATION PROVISION APPARATUS, AND COMPUTER-READABLE RECORDING MEDIUM | June 2017 | November 2019 | Abandon | 29 | 1 | 0 | No | No |
| 15534273 | GROUPING SYSTEM, GROUPING METHOD, AND GROUPING PROGRAM | June 2017 | December 2020 | Abandon | 42 | 2 | 0 | No | No |
| 15617996 | SYSTEMS AND METHODS FOR DETERMINING GEOGRAPHICAL SERVICE AREAS WITH BALANCED WORKLOAD | June 2017 | October 2023 | Abandon | 60 | 4 | 0 | Yes | Yes |
| 15616082 | SYSTEMS AND METHODS FOR ANALYZING CONSUMER SPENDING USING GEOFENCING | June 2017 | April 2021 | Allow | 46 | 3 | 0 | Yes | No |
| 15616518 | PROCESS MANAGEMENT FOR DOCUMENTATION-DRIVEN SOLUTION DEVELOPMENT AND AUTOMATED TESTING | June 2017 | August 2022 | Abandon | 60 | 6 | 0 | Yes | No |
| 15493162 | MOBILE BASED COMMON PLATFORM FOR OUTLET SPECIFIC CUSTOMER ENGAGEMENT | April 2017 | December 2021 | Abandon | 56 | 4 | 0 | Yes | Yes |
| 15488284 | SYSTEM AND METHOD FOR INFERRING SOCIAL INFLUENCE NETWORKS FROM TRANSACTIONAL DATA | April 2017 | November 2019 | Abandon | 31 | 1 | 0 | No | No |
| 15488231 | SYSTEM AND METHOD FOR IDENTIFYING TOPIC COVERAGE FOR A DISTRIBUTION PLATFORM THAT PROVIDES ACCESS TO ONLINE CONTENT ITEMS | April 2017 | April 2021 | Allow | 48 | 3 | 0 | Yes | No |
| 15487507 | COGNITIVE ORDER PROCESSING BY PREDICTING RESALABLE RETURNS | April 2017 | February 2021 | Allow | 46 | 4 | 0 | Yes | No |
| 15486875 | Systems and Methods for Thermal Monitoring in a Retail Facility | April 2017 | April 2021 | Abandon | 48 | 4 | 0 | No | No |
| 15444569 | METHOD AND SYSTEM FOR SEARCH PROVIDER SELECTION BASED ON PERFORMANCE SCORES WITH RESPECT TO EACH SEARCH QUERY | February 2017 | October 2021 | Allow | 55 | 6 | 0 | Yes | No |
| 15445809 | SYSTEMS AND METHODS FOR ACCESS CONTROL BASED ON MACHINE-LEARNING | February 2017 | July 2020 | Allow | 41 | 3 | 0 | Yes | No |
| 15444331 | News Delivery in Enterprise Setting | February 2017 | November 2020 | Abandon | 44 | 3 | 0 | No | No |
| 15445211 | COMPUTER-BASED FORECASTING OF MARKET DEMAND FOR A NEW PRODUCT | February 2017 | April 2021 | Abandon | 50 | 4 | 0 | Yes | No |
| 15507587 | METHOD AND SYSTEM FOR PROVIDING A DYNAMIC RIDE SHARING SERVICE | February 2017 | September 2020 | Abandon | 42 | 4 | 0 | Yes | No |
| 15439565 | SYSTEM AND METHOD FOR PROVIDING PREDICTIVE BEHAVIORAL ANALYTICS | February 2017 | September 2020 | Abandon | 43 | 5 | 0 | Yes | Yes |
| 15397113 | PROCESSING USER EXPERIENCE FEEDBACK IN A RETAIL ENVIRONMENT TO ASSIST CORRECTIVE ACTION | January 2017 | April 2021 | Abandon | 51 | 4 | 0 | Yes | No |
| 15365962 | INVENTORY DEMAND FORECASTING SYSTEM AND INVENTORY DEMAND FORECASTING METHOD | December 2016 | November 2019 | Abandon | 36 | 2 | 0 | No | No |
| 15366657 | MEETING TIME PICKER WITH AUTOMATED SUGGESTIONS | December 2016 | November 2019 | Abandon | 36 | 2 | 0 | No | No |
| 15367000 | MEETING TIME POLLING | December 2016 | October 2020 | Abandon | 46 | 4 | 0 | Yes | No |
This analysis examines appeal outcomes and the strategic value of filing appeals for examiner WALTON, CHESIREE A.
With a 33.3% reversal rate, the PTAB reverses the examiner's rejections in a meaningful percentage of cases. This reversal rate is above the USPTO average, indicating that appeals have better success here than typical.
Filing a Notice of Appeal can sometimes lead to allowance even before the appeal is fully briefed or decided by the PTAB. This occurs when the examiner or their supervisor reconsiders the rejection during the mandatory appeal conference (MPEP § 1207.01) after the appeal is filed.
In this dataset, 27.3% of applications that filed an appeal were subsequently allowed. This appeal filing benefit rate is below the USPTO average, suggesting that filing an appeal has limited effectiveness in prompting favorable reconsideration.
✓ Appeals to PTAB show good success rates. If you have a strong case on the merits, consider fully prosecuting the appeal to a Board decision.
⚠ Filing a Notice of Appeal shows limited benefit. Consider other strategies like interviews or amendments before appealing.
Examiner WALTON, CHESIREE A works in Art Unit 3624 and has examined 143 patent applications in our dataset. With an allowance rate of 29.4%, this examiner allows applications at a lower rate than most examiners at the USPTO. Applications typically reach final disposition in approximately 39 months.
Examiner WALTON, CHESIREE A's allowance rate of 29.4% places them in the 5% percentile among all USPTO examiners. This examiner is less likely to allow applications than most examiners at the USPTO.
On average, applications examined by WALTON, CHESIREE A receive 2.88 office actions before reaching final disposition. This places the examiner in the 80% percentile for office actions issued. This examiner issues more office actions than most examiners, which may indicate thorough examination or difficulty in reaching agreement with applicants.
The median time to disposition (half-life) for applications examined by WALTON, CHESIREE A is 39 months. This places the examiner in the 27% percentile for prosecution speed. Prosecution timelines are slightly slower than average with this examiner.
Conducting an examiner interview provides a +33.2% benefit to allowance rate for applications examined by WALTON, CHESIREE A. This interview benefit is in the 80% percentile among all examiners. Recommendation: Interviews are highly effective with this examiner and should be strongly considered as a prosecution strategy. Per MPEP § 713.10, interviews are available at any time before the Notice of Allowance is mailed or jurisdiction transfers to the PTAB.
When applicants file an RCE with this examiner, 15.7% of applications are subsequently allowed. This success rate is in the 14% percentile among all examiners. Strategic Insight: RCEs show lower effectiveness with this examiner compared to others. Consider whether a continuation application might be more strategic, especially if you need to add new matter or significantly broaden claims.
This examiner enters after-final amendments leading to allowance in 5.3% of cases where such amendments are filed. This entry rate is in the 7% percentile among all examiners. Strategic Recommendation: This examiner rarely enters after-final amendments compared to other examiners. You should generally plan to file an RCE or appeal rather than relying on after-final amendment entry. Per MPEP § 714.12, primary examiners have discretion in entering after-final amendments, and this examiner exercises that discretion conservatively.
When applicants request a pre-appeal conference (PAC) with this examiner, 0.0% result in withdrawal of the rejection or reopening of prosecution. This success rate is in the 17% percentile among all examiners. Note: Pre-appeal conferences show limited success with this examiner compared to others. While still worth considering, be prepared to proceed with a full appeal brief if the PAC does not result in favorable action.
This examiner withdraws rejections or reopens prosecution in 33.3% of appeals filed. This is in the 5% percentile among all examiners. Strategic Insight: This examiner rarely withdraws rejections during the appeal process compared to other examiners. If you file an appeal, be prepared to fully prosecute it to a PTAB decision. Per MPEP § 1207, the examiner will prepare an Examiner's Answer maintaining the rejections.
When applicants file petitions regarding this examiner's actions, 105.9% are granted (fully or in part). This grant rate is in the 94% percentile among all examiners. Strategic Note: Petitions are frequently granted regarding this examiner's actions compared to other examiners. Per MPEP § 1002.02(c), various examiner actions are petitionable to the Technology Center Director, including prematureness of final rejection, refusal to enter amendments, and requirement for information. If you believe an examiner action is improper, consider filing a petition.
Examiner's Amendments: This examiner makes examiner's amendments in 0.0% of allowed cases (in the 32% percentile). This examiner makes examiner's amendments less often than average. You may need to make most claim amendments yourself.
Quayle Actions: This examiner issues Ex Parte Quayle actions in 0.0% of allowed cases (in the 37% percentile). This examiner issues Quayle actions less often than average. Allowances may come directly without a separate action for formal matters.
Based on the statistical analysis of this examiner's prosecution patterns, here are tailored strategic recommendations:
Not Legal Advice: The information provided in this report is for informational purposes only and does not constitute legal advice. You should consult with a qualified patent attorney or agent for advice specific to your situation.
No Guarantees: We do not provide any guarantees as to the accuracy, completeness, or timeliness of the statistics presented above. Patent prosecution statistics are derived from publicly available USPTO data and are subject to data quality limitations, processing errors, and changes in USPTO practices over time.
Limitation of Liability: Under no circumstances will IronCrow AI be liable for any outcome, decision, or action resulting from your reliance on the statistics, analysis, or recommendations presented in this report. Past prosecution patterns do not guarantee future results.
Use at Your Own Risk: While we strive to provide accurate and useful prosecution statistics, you should independently verify any information that is material to your prosecution strategy and use your professional judgment in all patent prosecution matters.