Prosecution Insights
Last updated: April 19, 2026
Application No. 18/544,095

SYSTEMS AND METHODS FOR GENERATING A USER ATTRIBUTE SCORE

Non-Final OA §101
Filed
Dec 18, 2023
Examiner
GRANT, MICHAEL CHRISTOPHER
Art Unit
3715
Tech Center
3700 — Mechanical Engineering & Manufacturing
Assignee
Breakout Learning Inc.
OA Round
5 (Non-Final)
21%
Grant Probability
At Risk
5-6
OA Rounds
3y 8m
To Grant
28%
With Interview

Examiner Intelligence

Grants only 21% of cases
21%
Career Allow Rate
161 granted / 751 resolved
-48.6% vs TC avg
Moderate +7% lift
Without
With
+6.6%
Interview Lift
resolved cases with interview
Typical timeline
3y 8m
Avg Prosecution
74 currently pending
Career history
825
Total Applications
across all art units

Statute-Specific Performance

§101
30.3%
-9.7% vs TC avg
§103
33.2%
-6.8% vs TC avg
§102
12.1%
-27.9% vs TC avg
§112
19.6%
-20.4% vs TC avg
Black line = Tech Center average estimate • Based on career data from 751 resolved cases

Office Action

§101
DETAILED ACTION Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Continued Examination Under 37 CFR 1.114 A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 10/2/25 has been entered. Claim Rejections - 35 USC § 101 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 1, 3, 6-11, 13 and 16-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claims 1, 3, 6-11, 13 and 16-20 are directed to an abstract idea without significantly more. The claims recite a mental process that can be performed by human being and/or recite a method of organizing human activity and/or mathematical concepts and/or training/employing a machine learning model in a particular technological environment. In regard to Claims 1 and 11, the following limitations can be performed as a mental process by a human being in terms of claiming collecting data, analyzing that data, and providing outputs based on that analysis which has been held by the CAFC to be an abstract idea in decisions such as, e.g., Electric Power Group, University of Florida Research Foundation, and Yousician v Ubisoft (non-precedential); and/or recite a method of organizing human activity in terms of claiming the teaching/training/evaluation of a human subject’s which has been identified by MPEP 2106.04(a)(2)(II) as being a method of organizing human activity; and/or claim mathematical concepts; in terms of the Applicant claiming: [a] method of generating a user attribute score, the method comprising: receiving a discussion topic; and generating a first prompt as a function of the discussion topic by: training [a first algorithm] on a training dataset, wherein the training dataset correlates example discussion topics with example prompts; inputting the discussion topic into the [first algorithm]; receiving, as an output, from the [first algorithm], the first prompt; receiving feedback in a form of a cost function, wherein the feedback is used to train the [first algorithm]; wherein the [first algorithm] is configured to output prompts similar to the first prompt as a function of low-cost function values; and wherein the [first algorithm] is configured to output prompts dissimilar to the first prompt as a function of high- cost function values; presenting to a first user a first prompt […]; receiving from the first user device a first discussion datum, wherein the first discussion datum comprises a response by the first user to the first prompt; and generating a first user attribute score as a function of the first discussion datum by: training [a second algorithm] on a training dataset including example discussion data associated with example user attribute scores; generating an accuracy score for the second algorithm], wherein the accuracy score indicates a degree of retraining needed for the second algorithm]; comparing one or more new training examples of the accuracy score to a predetermined threshold; triggering retraining when the predetermined threshold is exceeded: retraining the second algorithm] as a function of the accuracy score until the accuracy score meets a predetermined threshold; inputting the first discussion datum into the second algorithm]; and receiving, as an output, from the second algorithm], the first user attribute score; determining a user group as a function of the first user attribute. In regard to Claims 1 and 11, Applicant claims training/employing a machine learning model in a particular technological environment, which was held to be abstract by the CAFC in, e.g., Recentiv Analytics. In regard to the dependent claims, they also claim an abstract idea to the extent that they merely claim further limitations that likewise could be performed as a mental process by a human being and/or claim mathematical concepts and/or claim training/employing a machine learning model in a particular technological environment. Furthermore, this judicial exception is not integrated into a practical application because to the extent that additional elements are claimed either alone or in combination such as, e.g., embodying Applicant’s abstract idea as computer software stored on a “memory” and executing on “a processor”, user devices, automatic speech recognition, a chatbot, and/or training/employing machine learning models, these are merely claimed to add insignificant extra-solution activity to the judicial exception (e.g., data gathering), to embody the abstract idea on a general purpose computer, and/or do no more than generally link the use of a judicial exception to a particular technological environment or field of use. In this regard, see MPEP 2106.04(d)(I) in regard to “courts have also identified limitations that did not integrate a judicial exception into a practical application…” Furthermore, the claims do not include additional elements that taken individually, and also taken as an ordered combination, are sufficient to amount to significantly more than the judicial exception because to the extent that, e.g., embodying Applicant’s abstract idea as computer software stored on a “memory” and executing on “a processor”, user devices, automatic speech recognition, a chatbot, and/or training/employing machine learning models, these are generic, well-known, and conventional elements and are claimed for the generic, well-known, and conventional functions of collecting and processing data and/or providing an analysis/outputs based on that processing. To the extent that an apparatus is claimed as an additional element said apparatus fails to qualify as a “particular machine” to the extent that it is claimed generally, merely implements the steps of Applicant’s claimed method, and is claimed merely for purposes of extra-solution activity or field of use. See MPEP 2106.05(b). As evidence that these additional elements are generic, well-known, and conventional, Applicant’s specification discloses the support for these elements in a manner that indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy 35 U.S.C. § 112(a). See, e.g., F7 in Applicant’s specification; see, e.g., p30 specifically in regard to automatic speech recognition; see, e.g., p132 in regard to a chatbot; and/or see, e.g., p57 and 72 regarding training/employing machine learning models. Response to Arguments Applicant argues in regard to the rejections made under 35 USC 101 that it has claimed patent eligible subject matter because its claimed subject matter cannot be practically performed in the human mind. Applicant’s claims may be characterized as being directed to collecting data (e.g., a discussion topic, discussion datum), analyzing that data (e.g., inputting the discussion topic into a first trained algorithm to generate a prompt, generating a first attribute score as a function of the discussion datum), and providing outputs based on that analysis (e.g., presenting the prompt to a user, determining a user group as a function of the user attribute score), and such subject matter has been held by the CAFC as being that which can be practically performed in the human mind. See MPEP 2106.04(a)(2)(III)(A). Applicant further argues in regard to the 101 rejections: PNG media_image1.png 392 658 media_image1.png Greyscale Applicant’s argument is unpersuasive. this Application is being examiner in Technology Center 3700 and the guidance memo does not apply to that Technology Center. What is more, it is unclear how to apply such guidance provided by the Office in this regard given that the Mayo test is a legal test and the Office as being part of the executive branch cannot make law. It is also unclear how to apply the Office’s guidance in this regard given that it is inapposite to precedential CAFC decisions. For example, the CAFC in Recentive Analytics held that a claim directed to, inter alia, PNG media_image2.png 131 458 media_image2.png Greyscale was patent ineligible under the Mayo test because claims directed to training/employing machine learning models in a particular technological environment were directed to an abstract idea. It is unclear, then, how the claimed limitations from, e.g., the Office’s Example 39 which are likewise directed to training a machine learning model using training data could possibly be directed to patent eligible subject matter given the CAFC’s opinion in Recentive. What is more, even if Applicant’s claimed limitations in regard to training/employing machine learning models in a particular technological environment are not considered to be abstract ideas they are also rejected, in the alternative, in the 101 rejection made supra as being claimed as elements in addition to Applicant’s claimed abstract ideas and not constituting “significantly more” and, thereby, also not rendering patent eligible subject matter under the Mayo test. Applicant’s specification contains basically one paragraph each disclosing how to train and/or use Applicant’s claimed “prompt generation machine learning model” and “attribute generation machine learning model”. Such limited disclosure could not possibly be enabling were these functions not already well-known, routine, and conventional and, as such, claiming the training and use of these models in addition to Applicant’s abstract ideas does not constitute “significantly more” and, thereby, fails to render patent eligible subject matter. Applicant argues that it does not claim a “method of organizing human activity”. Applicant’s argument is not persuasive to the extent that Applicant’s claims are directed to, inter alia, organizing groups of human students such that they can be taught/trained more effectively. See MPEP 2106.04(a)(2)(II). Applicant argues that it does not claim a mathematical concepts. Applicant’s argument is not persuasive to the extent that Applicant’s claims are directed to employing a “cost function”, which is a mathematical relationship. Applicant’s remaining arguments regarding “practical application” and “significantly more” are unpersuasive for the reasons already stated supra as well as because Applicant’s claimed invention is not directed to improving computer networking technology but is, instead, directed to collecting and analyzing data and then providing an output on a computer screen which (although it is not claimed) if it is viewed by a human being and if (although it is also not claimed) the prompt is then acted on by a human being may improve human learning. Such (theoretical) improvements to human performance are not patent eligible under the Mayo test. See, e.g., the CAFC’s opinion in Trading Technologies v. IBG LLC (2017-2257; 4/18/19), slip. op., page 9 (“This invention makes the trader faster and more efficient, not the computer. This is not a technical solution to a technical problem”, emphasis original). Conclusion The prior art made of record and not relied upon is listed in the attached PTO-Form 892 and is considered pertinent to applicant's disclosure. Any inquiry concerning this communication or earlier communications from the Examiner should be directed to Mike Grant whose telephone number is 571-270-1545. The Examiner can normally be reached on Monday through Friday between 8:00 a.m. and 5:00 p.m., except on the first Friday of each bi-week. If attempts to reach the Examiner by telephone are unsuccessful, the Examiner's Supervisory Primary Examiner, Peter Vasat can be reached at 571-270-7625. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /MICHAEL C GRANT/Primary Examiner, Art Unit 3715
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Prosecution Timeline

Dec 18, 2023
Application Filed
Mar 26, 2024
Non-Final Rejection — §101
Apr 17, 2024
Interview Requested
Apr 23, 2024
Examiner Interview Summary
Jun 25, 2024
Response Filed
Jul 01, 2024
Final Rejection — §101
Oct 07, 2024
Request for Continued Examination
Oct 11, 2024
Response after Non-Final Action
Jan 26, 2025
Non-Final Rejection — §101
Jul 30, 2025
Response Filed
Oct 01, 2025
Final Rejection — §101
Nov 04, 2025
Request for Continued Examination
Nov 16, 2025
Response after Non-Final Action
Jan 11, 2026
Non-Final Rejection — §101 (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

5-6
Expected OA Rounds
21%
Grant Probability
28%
With Interview (+6.6%)
3y 8m
Median Time to Grant
High
PTA Risk
Based on 751 resolved cases by this examiner. Grant probability derived from career allow rate.

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