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. The instant office action having application number 18034257, filed on April 27, 2023, has claims 1-20 pending in this application. Specification The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed. Claim Rejections - 35 USC § 112 The following is a quotation of 35 U.S.C. 112(b): (b) CONCLUSION.— The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention. The following is a quotation of 35 U.S.C. 112 (pre-AIA), second paragraph: The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention. Claim s 1 recites the limitation “the inference model” in line 6 . There is insufficient antecedent basis for this limitation in the claim. Claims 1 recites the limitation “the inference result ” in line 7 . There is insufficient antecedent basis for this limitation in the claim. Claims 1 recites the limitation “the user ” in line 9 . There is insufficient antecedent basis for this limitation in the claim. Same rejection applies to independent claims 6 and 7. 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 1-20 are rejected under 35 USC 101 because the claimed invention is directed to an abstract idea without significantly more. The claims are directed to a process (an act, or series of acts or steps), a machine (a concrete thing, consisting of parts, or of certain devices and combination of devices), and a manufacture (an article produced from raw or prepared materials by giving these materials new forms, qualities, properties, or combinations, whether by hand labor or by machinery). Thus, each of the claims falls within one of the four statutory categories (Step 1). With respect to claim 1, the limitations of “comparing target data to be inferred with a learning data group, wherein the target data represents data used for learning of the inference model; determining that the inference results uncertain when a comparison result does not satisfy a fixed criterion; and notifying the user that the interference result is uncertain in addition to the inference result when the inference result is determined to be uncertain.” , as drafted, is a process that, under its broadest reasonable interpretation, covers organizing human activities-- fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions) but for the recitation of generic computer components (Step 2A Prong 1). That is, other than reciting “ a processor”, nothing in the claim precludes these steps from practically being performed in the mind and/or by a human with pen and paper and organizing human activity. For example, but for the “by a processor” language, “comparing”, “determining” and “notifying” in the context of this claim encompasses the user manually organizing human activities (i.e. collaboration of users) within a creative action (i.e. art work creation between the users). If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation as a certain method of organizing human activities but for the recitation of generic computer components, then it falls within the “Certain Methods of Organizing Human Activities” grouping of abstract ideas. Accordingly, the claim(s) recite(s) an abstract idea. This judicial exception is not integrated into a practical application (Step 2A Prong Two). The “ comparing target data to be inferred with a learning data group ” is simply a post-solution data output of the aforementioned abstract idea. Next, the claim only recites one additional element “via the processor”. A computer-readable non-transitory recording medium” as recited in claim 7 are devoid of any structure whatsoever and thus only directed towards the abstract idea. The one or more processors in the steps is recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of electronic data query, retrieval and storage) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Specifically the claims amount to nothing more than an instruction to apply the abstract idea using a generic computer or invoking computers as tools by adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.04(d)(I) discussing MPEP 2106.05(f). The claims recitation of the “provide at least one user as a domain expert to the front-end interface” only generally linking the use of the judicial exception to a particular technological environment or field of use - see MPEP 2106.04(d)(I) discussing MPEP 2106.05(h}. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim(s) is/are directed to an abstract idea, even when considered as a whole. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception (Step 2B). A computer-readable non-transitory recording medium claim 7, again, is devoid of any structure whatsoever and thus only directed towards the abstract idea. As discussed above with respect to integration of the abstract idea into a practical application (Step 2A Prong 2), the additional element of using one or more processors to perform the steps amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claim(s) is/are not patent eligible, even when considered as a whole. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The insignificant extra-solution activity identified above, which include the data gathering steps, is recognized by the courts as well-understood, routine, and conventional activity when they are claimed in a merely generic manner ( e.g., at a high level of generality) or as insignificant extra-solution activity ( See MPEP 2106.05(d)(II)( i ) Receiving or transmitting data over a network, e.g., using the Internet to gather data, buySAFE , Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network) ). The claims are not patent eligible. Claims 2-5, 8-9, 10-14 and 15-20 depend on independent claim 1, 6 and 7; and hence, claims 2-5, 8-9, 10-14 and 15-20 recite the same as being the above abstract idea as well. Claim Rejections - 35 USC § 102 The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. Claims 1, 3-7, 11-13 and 16-19 are rejected under 35 USC 102(a)(1) as being anticipated by Erenrich et al. (US 2018/0330280 A1) (hereinafter Erenrich ). As per claim 1 , Erenrich discloses comparing target data to be inferred with a learning data group, wherein the target data represents data used for learning of the inference model [ entity resolution system 120 can be a computer system configured to execute software or a set of programmable instructions that collect or receive records from different lists and process those records to associate related records (comparing the records to be able to associate the records) to common entities that may not have useful identical fields while still excluding unrelated entity records, resulting in the identification of entity records that relate to a common entity , paragraph 26; applying a trained machine learning model to data samples to compute uncertainty scores based on model confidence , paragraphs 31-35] ; determining that the inference results uncertain when a comparison result does not satisfy a fixed criterion [ selecting samples whose uncertainty scores exceed a defined threshold, indicating low confidence or uncertainty , paragraphs 36-40] ; and notifying the user that the interference result is uncertain in addition to the inference result when the inference result is determined to be uncertain [ Figure 6 describe presenting high uncertainty examples to a user via a graphical user interface for review or labeling , paragraphs 45-50] . As per claim s 3 , 11 and 16 , wherein the data includes a discrete value, and the fixed criterion includes a number of data in which a discrete value of the learning data group matches a discrete value of the target data is equal to or larger than a reference number [ each record of first list 140 is depicted as a separate row in FIG. 2, it will be understood that each such record can be represented in other ways, for example, by a column or any other technique in the art. Also, first list 140 can include duplicate entities or duplicate sub-entities, as shown in rows 201 and 204. Each record can include several categories of information , paragraph 31] . As per claim s 4 , 12, 17 and 19 , Erenrich discloses wherein the inference model is a model that infers an objective variable from an explanatory variable, and the processor further configured to execute operations comprising: comparing a condition variable included in the target data and different from the explanatory variable with the condition variable included in each of the learning data groups [entity resolution system 120 can be a computer system configured to execute software or a set of programmable instructions that collect or receive records from different lists and process those records to associate related records , paragraph 26 ] ; and determining that the inference result is uncertain when a comparison result does not satisfy a fixed criterion [Figure 6 describe presenting high uncertainty examples to a user via a graphical user interface for review or labeling, paragraphs 45-50] . As per claim s 5 , 12 and 18 , Erenrich discloses comparing the target data in a future later than the target data to be inferred with the learning data group [entity resolution system 120 can be a computer system configured to execute software or a set of programmable instructions that collect or receive records from different lists and process those records to associate related records (comparing the records to be able to associate the records) to common entities that may not have useful identical fields while still excluding unrelated entity records, resulting in the identification of entity records that relate to a common entity, paragraph 26;applying a trained machine learning model to data samples to compute uncertainty scores based on model confidence, paragraphs 31-35] ; and determining that a future inference result is uncertain when a comparison result does not satisfy the fixed criterion [Figure 6 describe presenting high uncertainty examples to a user via a graphical user interface for review or labeling, paragraphs 45-50] ; and notifying the user that the future inference result is uncertain when the future inference result is determined to be uncertain [Figure 6 describe presenting high uncertainty examples to a user via a graphical user interface for review or labeling, paragraphs 45-50] . Allowable Subject Matter Claims 2, 8-9, 10, 14, 15 and 20 are objected to as being dependent upon a rejected base claim, but would be allowable if overcome the US 35 101 abstract idea and rewritten in independent form including all of the limitations of the base claim and any intervening claims. The following is a statement of reasons for the indication of allowable subject matter: The prior arts of record do not teach or suggest “ wherein the data includes a continuous value, and the fixed criterion includes a continuous value of the target data being less than or equal to a reference value corresponding to a maximum value of a continuous value of the learning data group and being greater than or equal to a reference value corresponding to a minimum value of the continuous value of the learning data group. ” Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to FILLIN "Examiner name" \* MERGEFORMAT NOOSHA ARJOMANDI whose telephone number is FILLIN "Phone number" \* MERGEFORMAT (571)272-9784 . The examiner can normally be reached on (571)272-9784 . 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, Robert Beausoliel can be reached on (571)272-3645 . 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.uspto.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. December 20, 2025 /NOOSHA ARJOMANDI/ Primary Examiner, Art Unit 2167