Prosecution Insights
Last updated: April 19, 2026
Application No. 18/239,709

EVALUATING MACHINE LEARNING (ML)-GENERATED PERSONALIZED RECOMMENDATIONS USING SHAPLEY ADDITIVE EXPLANATIONS (SHAP) VALUES

Non-Final OA §103
Filed
Aug 29, 2023
Examiner
ANYIKIRE, CHIKAODILI E
Art Unit
2487
Tech Center
2400 — Computer Networks
Assignee
Intuit Inc.
OA Round
1 (Non-Final)
75%
Grant Probability
Favorable
1-2
OA Rounds
3y 2m
To Grant
86%
With Interview

Examiner Intelligence

Grants 75% — above average
75%
Career Allow Rate
779 granted / 1042 resolved
+16.8% vs TC avg
Moderate +12% lift
Without
With
+11.5%
Interview Lift
resolved cases with interview
Typical timeline
3y 2m
Avg Prosecution
51 currently pending
Career history
1093
Total Applications
across all art units

Statute-Specific Performance

§101
3.7%
-36.3% vs TC avg
§103
46.3%
+6.3% vs TC avg
§102
36.9%
-3.1% vs TC avg
§112
1.5%
-38.5% vs TC avg
Black line = Tech Center average estimate • Based on career data from 1042 resolved cases

Office Action

§103
CTNF 18/239,709 CTNF 82637 DETAILED ACTION Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Claim Rejections - 35 USC § 103 07-06 AIA 15-10-15 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. 07-20-aia AIA The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. 07-23-aia AIA The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows: 1. Determining the scope and contents of the prior art. 2. Ascertaining the differences between the prior art and the claims at issue. 3. Resolving the level of ordinary skill in the pertinent art. 4. Considering objective evidence present in the application indicating obviousness or nonobviousness. 07-21-aia AIA Claim (s) 1, 7, 13 and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Karapentelakis et al (US 2024/0086766, hereafter Karapentelakis) in view of Schreiber et al (US 2022/0261549, hereafter Schreiber) . As per claim 1 , Karapentelakis discloses a method for selecting between a model output of a machine learning (ML) model and a generic output, comprising: processing user-specific data with the ML model to generate the model output and a model predicted score associated with the model output; calculating a Shapley Additive Explanations (SHAP) score (¶ 65); and providing the model output or the generic output as output from the ML model based on the SHAP score (¶ 65). However, Karapentelakis does not explicitly teach calculating a Shapley Additive Explanations (SHAP) score based on the model output, the model predicted score, and the user-specific data. In the same field of endeavor, Schreiber discloses calculating a Shapley Additive Explanations (SHAP) score based on the model output, the model predicted score, and the user-specific data (¶ 70). Therefore, it would have been obvious for one of ordinary skill in the art at the time the invention was effectively filed to modify the invention of Karapentelakis in view of Schreiber. The advantage is improving model accuracy. As per claim 7 , Karapentelakis discloses the method of Claim 1, wherein the model output generated by the ML model comprises a predicted output among a set of possible predicted outputs of the ML model determined using a highest-probability approach or a thresholding approach (¶ 39). Regarding claim 13 , arguments analogous to those presented for claim 1 are applicable for claim 13. Regarding claim 19 , arguments analogous to those presented for claim 7 are applicable for claim 19 . 07-21-aia AIA Claim (s) 6 and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Karapentelakis in view of Schreiber (hereafter Karapentelakis) in further view of Mishra et al (US 2023/0281047, hereafter Mishra) . As per claim 6 , Karapentelakis discloses the method of Claim 1. However, does not explicitly teach wherein calculating the SHAP score based on the model output, the model predicted score, and the user-specific data comprises: determining a SHAP value for each input feature in the user-specific data used to generate the model output and the model predicted score, wherein the user-specific data comprises one or more input features; and calculating a sum of the SHAP values determined for the one or more input features in the user-specific data, wherein the SHAP score comprises the sum. In the same field of endeavor, Mishra teaches wherein calculating the SHAP score based on the model output, the model predicted score, and the user-specific data comprises: determining a SHAP value for each input feature in the user-specific data used to generate the model output and the model predicted score, wherein the user-specific data comprises one or more input features; and calculating a sum of the SHAP values determined for the one or more input features in the user-specific data, wherein the SHAP score comprises the sum (¶ 120). Therefore, it would have been obvious for one of ordinary skill in the art at the time the invention was effectively filed to modify the invention of Karapentelakis in further view of Frank. The advantage is improving user experience. Regarding claim 18 , arguments analogous to those presented for claim 6 are applicable for claim 18 . Allowable Subject Matter 12-151-08 AIA 07-43 12-51-08 Claim (s) 2 - 5, 8, 14 - 17, and 20 objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. 12-151-07 AIA 07-97 12-51-07 Claim (s) 9 - 12 allowed. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHIKAODILI E ANYIKIRE whose telephone number is (571)270-1445. The examiner can normally be reached 8 am - 4:30 pm. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, David Czekaj can be reached at 571-272-7327. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /CHIKAODILI E ANYIKIRE/Primary Examiner, Art Unit 2487 Application/Control Number: 18/239,709 Page 2 Art Unit: 2487 Application/Control Number: 18/239,709 Page 3 Art Unit: 2487 Application/Control Number: 18/239,709 Page 4 Art Unit: 2487 Application/Control Number: 18/239,709 Page 5 Art Unit: 2487 Application/Control Number: 18/239,709 Page 6 Art Unit: 2487
Read full office action

Prosecution Timeline

Aug 29, 2023
Application Filed
Mar 12, 2026
Non-Final Rejection — §103 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
75%
Grant Probability
86%
With Interview (+11.5%)
3y 2m
Median Time to Grant
Low
PTA Risk
Based on 1042 resolved cases by this examiner. Grant probability derived from career allow rate.

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