Prosecution Insights
Last updated: October 04, 2026
Application No. 17/404,011

METHOD, ELECTRONIC DEVICE, AND COMPUTER PROGRAM PRODUCT FOR SAMPLE MANAGEMENT

Final Rejection §101
Filed
Aug 17, 2021
Priority
Jul 23, 2021 — CN 202110836667.5
Examiner
PHUNG, STEVEN HUYNH
Art Unit
2125
Tech Center
2100 — Computer Architecture & Software
Assignee
EMC IP Holding Company LLC
OA Round
4 (Final)
74%
Grant Probability
Favorable
5-6
OA Rounds
0m
Est. Remaining
99%
With Interview

Examiner Intelligence

Grants 74% — above average
74%
Career Allowance Rate
34 granted / 46 resolved
+18.9% vs TC avg
Strong +30% interview lift
Without
With
+30.2%
Interview Lift
resolved cases with interview
Typical timeline
4y 5m
Avg Prosecution
14 currently pending
Career history
69
Total Applications
across all art units

Statute-Specific Performance

§101
32.2%
-7.8% vs TC avg
§103
38.6%
-1.4% vs TC avg
§102
9.9%
-30.1% vs TC avg
§112
18.4%
-21.6% vs TC avg
Black line = Tech Center average estimate • Based on career data from 46 resolved cases

Office Action

§101
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 . Response to Amendment In the previous Office Action issued March 12, 2026 (hereinafter “the previous Office Action”), claims 1-20 were pending. This action is in response to the amendment and remarks filed June 11, 2026. In the amendment, claims 1, 9, and 17 were amended, no claims were canceled, and no claims were added. Thus, claims 1-20 are pending. Information Disclosure Statement The information disclosure statement (IDS) submitted on July 13, 2026, is being considered by the examiner. Claim Rejections - 35 USC § 101 The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action. Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Step 1: Claims 1-8 are directed to a method [process]. Claims 9-16 are directed to an electronic device [machine]. Claims 17-20 are directed to a computer program product [machine]. Regarding Claim 1: Step 2A, Prong 1: The following limitations are directed to the abstract idea of a mental process [see MPEP 2106.04(a)(2) III. C.]. In particular, the claim recites mental processes that are concepts performed in the human mind or with pen and paper (including an observation, evaluation, judgement, or opinion). (a) determining…a first set of distilled samples from a first set of samples based on a characteristic distribution of the first set of samples, the number of samples in the first set of distilled samples being less than that of the first set of samples, and the first set of samples being associated with a first set of classifications (b) acquiring…a first set of characteristic representations associated with the first set of distilled samples, wherein the acquiring comprises processing the first set of distilled samples…to extract the characteristic representations from the first set of distilled samples (c) adjusting…the first set of characteristic representations so that a distance between characteristic representations associated with the same classification is less than a predetermined threshold (d) …transform characteristic vectors of respective ones of the first set of characteristic representations from a first characteristic space to a second characteristic space different than the first characteristic space (f) determining…based on the adjusted first set of characteristic representations, a first set of classification characteristics of the first set of samples associated with the first set of classifications, the classification characteristics being used to characterize a distribution of characteristic representations of samples having corresponding classifications in the first set of samples As drafted, under their broadest reasonable interpretation (BRI), in view of the specification, the above limitations cover concepts performed in the human mind (observation, evaluation, judgement, or opinion). Given a sufficiently small set of data, nothing in the claim prohibits this process from being performed mentally or with pen and paper. The following limitations are directed to the abstract idea of a mathematical concept (i.e., mathematical relationships, mathematical formulas or equations, or mathematical calculations) [see MPEP 2106.04(a)(2) I.C.]. (e) …back propagation of a loss function configured to iteratively combine results of an application of a designated transformation function to distances between respective pairs of the characteristic vectors, the loss function determining for each of the pairs a difference between (i) a first function of a corresponding one of the distances and at least one adjustable hyperparameter and (ii) a second function of the corresponding one of the distances and the at least one adjustable hyperparameter, the second function being different than the first function Step 2A, Prong 2: There are no additional elements in this claim that integrate the judicial exception into a practical application. The following additional elements are adding the words “apply it” (or an equivalent) with the judicial exception, 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 2106.05(f)], and therefore fails to integrate the judicial exception into a practical application. (a) …in a processor-based machine learning system comprising a serial processing pipeline including a pre-trained machine learning model having an output coupled to an input of a spatial transformation machine learning model… (b) …utilizing the pre-trained machine learning model in the serial processing pipeline of the processor-based machine learning system…through the pre-trained machine learning model in the serial processing pipeline of the processor-based machine learning system… (c) …utilizing the spatial transformation machine learning model in the serial processing pipeline of the processor-based machine learning system… (d) the spatial transformation machine learning model being configured to… (e) the training of the spatial transformation machine learning model to transform the characteristic vectors from the first characteristic space to the second characteristic space comprising adjusting entries of a transformation matrix of the spatial transformation machine learning model by… (f) …in the process-based machine learning system… training a classifier of the processor-based machine learning system based at least in part on the classification characteristics The following additional elements are directed to insignificant extra-solution activity to the judicial exception [see MPEP 2106.05(g)]. wherein adjusting the first set of characteristic representations comprises training the spatial transformation machine learning model by iterative processing in at least one processor of the processor-based machine learning system Step 2B: There are no additional elements in this claim that amount to significantly more than the judicial exception. The following additional elements are adding the words “apply it” (or an equivalent) with the judicial exception, 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 2106.05(f)], and therefore fails to amount to significantly more than the judicial exception. (a) …in a processor-based machine learning system comprising a serial processing pipeline including a pre-trained machine learning model having an output coupled to an input of a spatial transformation machine learning model… (b) …utilizing the pre-trained machine learning model in the serial processing pipeline of the processor-based machine learning system…through the pre-trained machine learning model in the serial processing pipeline of the processor-based machine learning system… (c) …utilizing the spatial transformation machine learning model in the serial processing pipeline of the processor-based machine learning system… (d) the spatial transformation machine learning model being configured to… (e) the training of the spatial transformation machine learning model to transform the characteristic vectors from the first characteristic space to the second characteristic space comprising adjusting entries of a transformation matrix of the spatial transformation machine learning model by… (f) …in the process-based machine learning system… training a classifier of the processor-based machine learning system based at least in part on the classification characteristics The following additional element is directed to performing repetitive calculations. The courts have recognized performing repetitive calculations as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity to the judicial exception [see MPEP 2106.05(d) II.]. wherein adjusting the first set of characteristic representations comprises training the spatial transformation machine learning model by iterative processing in at least one processor of the processor-based machine learning system Regarding Claim 2: Step 2A, Prong 1: The claim recites the same abstract ideas as in claim 1. The following limitations are/remain directed to the abstract idea of a mental process [see MPEP 2106.04(a)(2) III. C.]. In particular, the claim recites mental processes that are concepts performed in the human mind (including an observation, evaluation, judgement, or opinion). wherein determining the first set of classification characteristics based on one set of distillations and based on classification characteristics of the first set of characteristic representations comprises: acquiring one set of distillation classification characteristics of the adjusted first set of characteristic representations determining the first set of classification characteristics based on one set of distillations and based on classification characteristics of the first set of characteristic representations Step 2A, Prong 2: There are no additional elements in this claim that integrate the judicial exception into a practical application. Step 2B: There are no additional elements in this claim that amount to significantly more than the judicial exception. Regarding Claim 3: Step 2A, Prong 1: The claim recites the same abstract ideas as in claim 1. The following limitations are directed to the abstract idea of a mental process [see MPEP 2106.04(a)(2) III. C.]. In particular, the claim recites mental processes that are concepts performed in the human mind (including an observation, evaluation, judgement, or opinion). acquiring a second set of samples, the second set of samples being associated with a second set of classifications determining, at least based on the first set of classification characteristics, a second set of classification characteristics of a third set of samples associated with a third set of classifications, the third set of samples being a union of the first set of samples and the second set of samples, and the third set of classifications being a union of the first set of classifications and the second set of classifications Step 2A, Prong 2: There are no additional elements in this claim that integrate the judicial exception into a practical application. Step 2B: There are no additional elements in this claim that amount to significantly more than the judicial exception. Regarding Claim 4: Step 2A, Prong 1: The claim recites the same abstract ideas as in claim 3. The following limitations are/remain directed to the abstract idea of a mental process [see MPEP 2106.04(a)(2) III. C.]. In particular, the claim recites mental processes that are concepts performed in the human mind (including an observation, evaluation, judgement, or opinion). wherein determining the second set of classification characteristics at least based on the first set of classification characteristics comprises: constructing one set of intermediate samples based on the first set of classification characteristics in response to determining that the first set of classifications is different from the second set of classifications determining a second set of distilled samples from a union of the set of intermediate samples and the second set of samples determining, based on characteristic representations associated with the second set of distilled samples, the second set of classification characteristics of the third set of samples associated with the third set of classifications Step 2A, Prong 2: There are no additional elements in this claim that integrate the judicial exception into a practical application. Step 2B: There are no additional elements in this claim that amount to significantly more than the judicial exception. Regarding Claim 5: Step 2A, Prong 1: The claim recites the same abstract ideas as in claim 3. The following limitations are/remain directed to the abstract idea of a mental process [see MPEP 2106.04(a)(2) III. C.]. In particular, the claim recites mental processes that are concepts performed in the human mind (including an observation, evaluation, judgement, or opinion). wherein determining the second set of classification characteristics at least based on the first set of classification characteristics comprises: determining a second set of characteristic representations associated with the second set of samples in response to determining that the first set of classifications is the same as the second set of classifications determining a third set of classification characteristics of the second set of samples associated with the first set of classifications using the first set of classification characteristics and based on a transformation between the adjusted first set of characteristic representations and the adjusted second set of characteristic representations determining the second set of classification characteristics based on the first set of classification characteristics and the third set of classification characteristics Step 2A, Prong 2: There are no additional elements in this claim that integrate the judicial exception into a practical application. Step 2B: There are no additional elements in this claim that amount to significantly more than the judicial exception. Regarding Claim 6: Step 2A, Prong 1: The claim recites the same abstract ideas as in claim 1. The following limitations are directed to the abstract idea of a mental process [see MPEP 2106.04(a)(2) III. C.]. In particular, the claim recites mental processes that are concepts performed in the human mind (including an observation, evaluation, judgement, or opinion). acquiring target samples and determining characteristic representations associated with the target samples determining target classifications associated with the target samples from the first set of classifications based on a comparison between the characteristic representations and the first set of classification characteristics Step 2A, Prong 2: There are no additional elements in this claim that integrate the judicial exception into a practical application. Step 2B: There are no additional elements in this claim that amount to significantly more than the judicial exception. Regarding Claim 7: Step 2A, Prong 1: The claim recites the same abstract ideas as in claim 1. The following limitations remain directed to the abstract idea of a mental process [see MPEP 2106.04(a)(2) III. C.]. In particular, the claim recites mental processes that are concepts performed in the human mind (including an observation, evaluation, judgement, or opinion). wherein the classification characteristics comprise a mean value and a covariance of the distribution of characteristic representations of samples having corresponding classifications in the first set of samples Step 2A, Prong 2: There are no additional elements in this claim that integrate the judicial exception into a practical application. Step 2B: There are no additional elements in this claim that amount to significantly more than the judicial exception. Regarding Claim 8: Step 2A, Prong 1: The claim recites the same abstract ideas as in claim 1. The following limitations are/remain directed to the abstract idea of a mental process [see MPEP 2106.04(a)(2) III. C.]. In particular, the claim recites mental processes that are concepts performed in the human mind (including an observation, evaluation, judgement, or opinion). wherein determining the first set of distilled samples from the first set of samples based on the characteristic distribution of the first set of samples comprises: acquiring a second set of samples, the second set of samples being associated with a second set of classifications performing an adjustment on the at least one set of characteristic representations such that the at least one set of characteristic representations is transformed into a characteristic representation space determining the first set of distilled samples from the first set of samples based on a distribution of the adjusted at least one set of characteristic representations in the characteristic representation space Step 2A, Prong 2: There are no additional elements in this claim that integrate the judicial exception into a practical application. Step 2B: There are no additional elements in this claim that amount to significantly more than the judicial exception. Regarding Claim 9: Claim 9 corresponds to claim 1. Step 2A, Prong 1: The claim recites the same abstract ideas as in claim 1. Step 2A, Prong 2: There are no additional elements in this claim that integrate the judicial exception into a practical application. The analysis of claim 9 at this step mirror that of claim 1, with the exception the following limitations. The following additional elements are 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 2106.05(f)] and therefore fails to integrate the judicial exception into a practical application. An electronic device, comprising: at least one processor, and memory coupled to the at least one processor, the memory having instructions stored therein that, when executed by the at least one processor, cause the electronic device to execute actions comprising: Step 2B: There are no additional elements in this claim that amount to significantly more than the judicial exception. The analysis of claim 9 at this step mirror that of claim 1, with the exception the following limitations. The following additional elements are 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 2106.05(f)] and therefore fails to amount to significantly more than the judicial exception. An electronic device, comprising: at least one processor, and memory coupled to the at least one processor, the memory having instructions stored therein that, when executed by the at least one processor, cause the electronic device to execute actions comprising: Regarding Claim 10: Step 2A, Prong 1: The claim recites the same abstract ideas as in claim 9. The following limitations are/remain directed to the abstract idea of a mental process [see MPEP 2106.04(a)(2) III. C.]. In particular, the claim recites mental processes that are concepts performed in the human mind (including an observation, evaluation, judgement, or opinion). wherein determining the first set of classification characteristics of the first set of samples associated with the first set of classifications comprises: acquiring classification characteristics of the adjusted first set of characteristic representations determining the first set of classification characteristics using the unscented Kalman filtering algorithm and based on the classification characteristics of the first set of characteristic representations Step 2A, Prong 2: There are no additional elements in this claim that integrate the judicial exception into a practical application. Step 2B: There are no additional elements in this claim that amount to significantly more than the judicial exception. Regarding Claims 11-16: Claims 11-16 correspond to claims 3-8. In particular, 11:3, 12:4, 13:5, 14:6, 15:7, 16:8. Step 2A, Prong 1: Claims 11-16 recites the same abstract ideas as in claims 3-8. Step 2A, Prong 2: There are no additional elements in this claim that integrate the judicial exception into a practical application. The analysis of claims 11-16 at this step mirror that of claims 3-8. Step 2B: There are no additional elements in this claim that amount to significantly more than the judicial exception. The analysis of claims 11-16 at this step mirror that of claims 3-8. Regarding Claim 17: Claim 17 corresponds to claim 1. Step 2A, Prong 1: The claim recites the same abstract ideas as in claim 1. Step 2A, Prong 2: There are no additional elements in this claim that integrate the judicial exception into a practical application. The analysis of claim 17 at this step mirror that of claim 1, with the exception the following limitations. The following additional elements are 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 2106.05(f)] and therefore fails to integrate the judicial exception into a practical application. A computer program product comprising a non-transitory computer-readable medium having machine-executable instructions stored therein, wherein the machine-executable instructions, when executed by a machine, cause the machine to perform actions comprising: Step 2B: There are no additional elements in this claim that amount to significantly more than the judicial exception. The analysis of claim 17 at this step mirror that of claim 1, with the exception the following limitations. The following additional elements are 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 2106.05(f)] and therefore fails to amount to significantly more than the judicial exception. A computer program product comprising a non-transitory computer-readable medium having machine-executable instructions stored therein, wherein the machine-executable instructions, when executed by a machine, cause the machine to perform actions comprising: Regarding Claims 18-20: Claims 18-20 correspond to claims 2-4. In particular, 18:2, 19:3, 20:4. Step 2A, Prong 1: Claims 18-20 recites the same abstract ideas as in claims 2-4. Step 2A, Prong 2: There are no additional elements in this claim that integrate the judicial exception into a practical application. The analysis of claims 18-20 at this step mirror that of claims 2-4. Step 2B: There are no additional elements in this claim that amount to significantly more than the judicial exception. The analysis of claims 18-20 at this step mirror that of claims 2-4. Response to Arguments Applicant's arguments filed June 11, 2026 (“Remarks”) have been fully considered but they are not persuasive. 35 U.S.C. § 101: Remarks pp. 12-15. Applicant argues claim 1 cannot be construed as reciting an abstract idea, and claim 1 integrates any such abstract idea into a practical application that provides improvements in computer technology. Applicant argues claim 1 does not recite mental processes. In particular, Applicant argues two examples from the claim that cannot be performed in the human mind. Regarding the first example, processing a first set of distilled samples to extract characteristic representations is mentally performable, i.e. evaluation. The claim additionally recites performing the processing using a pre-trained model of a processor-based machine learning system, but the model usage is recited at a high level, and thus analyzed as mere instructions to implement the abstract idea on a computer. Next, Applicant argues that iteratively processing a loss function cannot practically be performed in the human mind. Examiner respectfully disagrees. The loss function recited in the claim is directed to a mathematical concept, i.e. mathematical formula. On the other hand, the spatial transformation machine learning model is recited at a high level, and thus analyzed as mere instruction to apply the abstract idea on a computer. Lastly, the iterative process is directed to performing repetitive calculations, and repetitive calculations have been recognized to be well understood, routine, and conventional activities when recited in a merely generic manner. Therefore, claim 1 recites abstract ideas and additional elements. Applicant further argues regarding the practical application. Examiner respectfully disagrees with Applicant’s interpretation of claim 1. The mental processes cited above in claim 1 are claim limitations that can be practically performed by the human mind. Although the claims recite the use of machine learning models, the machine learning models in the claims are recited in a merely generic manner. Therefore, the additional elements do not integrate the abstract ideas into a practical application that provides improvements to computer technology. Conclusion Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to STEVEN PHUNG whose telephone number is (703) 756-1499. The examiner can normally be reached Monday-Thursday: 9:00AM-4:00PM ET. 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, KAMRAN AFSHAR can be reached at (571) 272-7796. 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. /S.H.P./Examiner, Art Unit 2125 /KAMRAN AFSHAR/Supervisory Patent Examiner, Art Unit 2125
Read full office action

Prosecution Timeline

Show 2 earlier events
Jun 11, 2025
Response Filed
Sep 25, 2025
Final Rejection mailed — §101
Nov 24, 2025
Response after Non-Final Action
Dec 22, 2025
Request for Continued Examination
Jan 15, 2026
Response after Non-Final Action
Mar 12, 2026
Non-Final Rejection mailed — §101
Jun 11, 2026
Response Filed
Aug 24, 2026
Final Rejection mailed — §101 (current)

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Prosecution Projections

5-6
Expected OA Rounds
74%
Grant Probability
99%
With Interview (+30.2%)
4y 5m (~0m remaining)
Median Time to Grant
High
PTA Risk
Based on 46 resolved cases by this examiner. Grant probability derived from career allowance rate.

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