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Paper Citation Record · LEDGER

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection

As of 23 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 1 inbound Pith citation observation for arXiv:2607.13387.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2607.13387 v1

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T05:24:23.028428Z

measured 54 of 54 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T04:44:23.868636Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-14T04:44:24.153705Z

Reference resolution

53 of 53 outbound references displayed

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Outbound references

Observation 40e2e469-a715-4a6a-ba50-9da6219999bf · outbound

This paper cites Bar-Shalom, X.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Bar-Shalom, X

Reference 1

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Observation 41fe5a36-47dd-4a60-809f-952b4d4a65f8 · outbound

This paper cites Tracking targets using adaptive kalman filter- ing,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Tracking targets using adaptive kalman filter- ing,

Reference 2

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Observation 53e639a8-6042-4544-a590-7f4db662151e · outbound

This paper cites Durbin and S.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Durbin and S

Reference 3

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Observation 34b6ec6b-eee8-4ac0-92de-86f5684ac4b3 · outbound

This paper cites The Kalman filter,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection The Kalman filter,

Reference 4

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Observation dc113d8d-d1cb-427a-9884-ce339ed5578a · outbound

This paper cites A new approach to linear filtering and prediction problems,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection A new approach to linear filtering and prediction problems,

Reference 5

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Observation 3e8b3e5b-d5c4-4ede-871c-049dfc4fdd73 · outbound

This paper cites The Kalman filter-its recognition and development for aerospace applications,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection The Kalman filter-its recognition and development for aerospace applications,

Reference 6

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Observation 89f0af0d-0f59-43f7-9381-6b1f44394242 · outbound

This paper cites Unscented filtering and nonlinear estimation,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Unscented filtering and nonlinear estimation,

Reference 7

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Observation c2e31b84-2249-46ae-80bd-82a1d70a28c6 · outbound

This paper cites Artificial intelligence-aided Kalman filters: AI-augmented designs for Kalman-type algorithms,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Artificial intelligence-aided Kalman filters: AI-augmented designs for Kalman-type algorithms,

Reference 8

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Observation 26067421-1345-488e-b038-188f3e009c4c · outbound

This paper cites Model-based deep learning,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Model-based deep learning,

Reference 9

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Observation 8468f518-aca8-4ec2-9e64-98bef1894c07 · outbound

This paper cites Augmented physics-based machine learning for navigation and tracking,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Augmented physics-based machine learning for navigation and tracking,

Reference 10

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Observation c293af3b-0e09-47c3-86a6-ab382d5c4ffd · outbound

This paper cites Learning nonlinear state–space models using autoencoders,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Learning nonlinear state–space models using autoencoders,

Reference 11

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Observation a9681b29-249d-44c9-95e6-d46b86f03bfa · outbound

This paper cites NNAKF: A neural network adapted Kalman filter for target tracking,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection NNAKF: A neural network adapted Kalman filter for target tracking,

Reference 12

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Observation 44dddf4a-a956-4dfb-add4-7374b0441d52 · outbound

This paper cites EKFNet: Learning system noise covariance parameters for nonlinear tracking,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection EKFNet: Learning system noise covariance parameters for nonlinear tracking,

Reference 13

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Observation bd064c2a-cbfc-4664-9a11-ffa9293b1638 · outbound

This paper cites Adaptive Kalman-informed transformer,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Adaptive Kalman-informed transformer,

Reference 14

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Observation 2f3a54a0-5a7a-47ec-82e8-de09a09c5cb0 · outbound

This paper cites Combining generative and discriminative models for hybrid inference,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Combining generative and discriminative models for hybrid inference,

Reference 15

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Observation a4003d09-cf0e-4c25-bf37-e0d05f355f90 · outbound

This paper cites Neural augmentation of Kalman filter with hypernetwork for channel tracking,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Neural augmentation of Kalman filter with hypernetwork for channel tracking,

Reference 16

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Observation 200d6e6f-c716-4e3e-8e05-35ecf4db3e0d · outbound

This paper cites DANSE: Data-driven non-linear state estimation of model-free process in unsupervised learning setup,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection DANSE: Data-driven non-linear state estimation of model-free process in unsupervised learning setup,

Reference 17

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Observation 40646797-e5e4-42b9-bacf-88896551a28e · outbound

This paper cites DeepBayes—an estimator for parameter estimation in stochastic nonlinear dynamical models,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection DeepBayes—an estimator for parameter estimation in stochastic nonlinear dynamical models,

Reference 18

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Observation 500308ce-4bd5-4876-a840-460173f3b96a · outbound

This paper cites KalmanNet: Neural network aided Kalman filtering for partially known dynamics,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection KalmanNet: Neural network aided Kalman filtering for partially known dynamics,

Reference 19

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Observation 17409652-63b3-463b-96cb-e42c63492f8b · outbound

This paper cites RTSNet: Learning to smooth in partially known state-space models,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection RTSNet: Learning to smooth in partially known state-space models,

Reference 20

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Observation 15a15f90-114e-4499-84ec-d838b5ca0347 · outbound

This paper cites Split-KalmanNet: A robust model-based deep learning approach for state estimation,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Split-KalmanNet: A robust model-based deep learning approach for state estimation,

Reference 21

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Observation 3fc58190-dbeb-4ba2-a5b1-fbd2709a1abb · outbound

This paper cites Latent-KalmanNet: Learned Kalman filtering for tracking from high-dimensional signals,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Latent-KalmanNet: Learned Kalman filtering for tracking from high-dimensional signals,

Reference 22

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Observation 48027f47-f6c1-4fbe-a6d2-b68810727809 · outbound

This paper cites Nonlinear Kalman Filtering based on Self-Attention Mechanism and Lattice Trajectory Piecewise Linear Approximation.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Nonlinear Kalman Filtering based on Self-Attention Mechanism and Lattice Trajectory Piecewise Linear Approximation

Reference 23

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Observation ec98f7a3-3832-49bb-a046-09bef9bca200 · outbound

This paper cites GSP-KalmanNet: Tracking graph signals via neural-aided Kalman filtering,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection GSP-KalmanNet: Tracking graph signals via neural-aided Kalman filtering,

Reference 24

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Observation 8824f6b1-0e88-4c6f-a2d1-198e5c912371 · outbound

This paper cites Energy-Efficient State Estimation with 1-Bit Sensing: A Bussgang-Kalman Framework for Internet of Things.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Energy-Efficient State Estimation with 1-Bit Sensing: A Bussgang-Kalman Framework for Internet of Things

Reference 25

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Observation 6741a7cc-2908-405c-8c18-8c829d951172 · outbound

This paper cites Discriminative and generative learning for linear estimation of random signals [lecture notes],.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Discriminative and generative learning for linear estimation of random signals [lecture notes],

Reference 26

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Observation 05cfbdad-7156-4c49-973d-362e13800337 · outbound

This paper cites Towards Out-Of-Distribution Generalization: A Survey.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Towards Out-Of-Distribution Generalization: A Survey

Reference 27

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Observation d6eaaf2c-efdb-42c0-a64a-173661ed7553 · outbound

This paper cites Adaptive KalmanNet: Data-driven Kalman filter with fast adaptation,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Adaptive KalmanNet: Data-driven Kalman filter with fast adaptation,

Reference 28

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Observation 7b6898da-693d-49ae-a7f2-538e3b78769e · outbound

This paper cites EM-Kalmannet: AI-aided kalman tracking in partially known time-varying state-space models,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection EM-Kalmannet: AI-aided kalman tracking in partially known time-varying state-space models,

Reference 29

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Observation 10667ae4-515a-4305-82d1-b8eba1285124 · outbound

This paper cites MAML- KalmanNet: A neural network-assisted Kalman filter based on model-agnostic meta-learning,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection MAML- KalmanNet: A neural network-assisted Kalman filter based on model-agnostic meta-learning,

Reference 30

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Observation 1bcab060-85fb-430b-9ced-6ed7527f25a7 · outbound

This paper cites Approaches to adaptive filtering,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Approaches to adaptive filtering,

Reference 31

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Observation 6b751d80-c859-4a66-a1cc-c88f49af7e86 · outbound

This paper cites An approach to time series smoothing and forecasting using the EM algorithm,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection An approach to time series smoothing and forecasting using the EM algorithm,

Reference 32

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Observation 8693189e-6fa3-4c5d-883a-346d6b2afab5 · outbound

This paper cites Variational adaptive Kalman filter with Gaussian-Inverse-Wishart mixture distribution,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Variational adaptive Kalman filter with Gaussian-Inverse-Wishart mixture distribution,

Reference 33

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Observation 4c88c28b-d82b-4e06-8b19-a64286d5301c · outbound

This paper cites A novel robust Kalman filtering framework based on normal-skew mixture distribution,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection A novel robust Kalman filtering framework based on normal-skew mixture distribution,

Reference 34

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Observation 6d9f4287-3f67-4c6b-a3d7-487e3b15c6b5 · outbound

This paper cites Distributed generalized minimum error entropy unscented Kalman filter under hybrid attacks without prior knowledge,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Distributed generalized minimum error entropy unscented Kalman filter under hybrid attacks without prior knowledge,

Reference 35

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Observation 0181ce41-1a00-4c3e-bd11-373eae03d070 · outbound

This paper cites Variational nonlinear Kalman filtering with unknown process noise covariance,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Variational nonlinear Kalman filtering with unknown process noise covariance,

Reference 36

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Observation edf41001-01c0-4b35-87f0-130faf4b8b0d · outbound

This paper cites Asynchronous online adaptation via modular drift detection for deep receivers,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Asynchronous online adaptation via modular drift detection for deep receivers,

Reference 37

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Observation fe1196b0-d73a-4200-abbf-336a93cfc5e8 · outbound

This paper cites University of Michigan north campus long-term vision and lidar dataset,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection University of Michigan north campus long-term vision and lidar dataset,

Reference 38

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Observation 17ca4ac5-861a-4f4a-a052-fe5bc96ec52c · outbound

This paper cites Cubature Kalman filters,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Cubature Kalman filters,

Reference 39

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source=pdf_text observed=2026-08-02T05:24:21.443420Z digest=sha256:1008b90aa679e9480f971e1b31c7c763a5bd4a6f53fc1a311853936129513dec

Observation f23ad82c-5388-4117-8150-8d5ee3ba5266 · outbound

This paper cites Model-based deep learning,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Model-based deep learning,

Reference 40

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source=pdf_text observed=2026-08-02T05:24:21.590926Z digest=sha256:55afa5e76a6ed877c6f91b1f3a80d11c15852119aa38ee8657960ccfaaeb1cc2

Observation 957951a3-d79a-49d6-afd2-a79587977772 · outbound

This paper cites A survey of methods for time series change point detection,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection A survey of methods for time series change point detection,

Reference 41

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source=pdf_text observed=2026-08-02T05:24:21.648166Z digest=sha256:69b597a4b7b95f917dcc6db695c1f7f1989f5dca9f5128cc2d8fe77a236d918a

Observation a566d0bb-789e-4df4-b046-5af780576ea9 · outbound

This paper cites Bayesian Online Changepoint Detection.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Bayesian Online Changepoint Detection

Reference 42

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Observation 59d0bd4c-460a-44fa-8233-0cdccc4bfe8a · outbound

This paper cites Restarted Bayesian online change-point detector achieves optimal detection delay,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Restarted Bayesian online change-point detector achieves optimal detection delay,

Reference 43

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Observation 94e82f74-204e-4546-9a89-0347497673ee · outbound

This paper cites Kernel change-point analysis,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Kernel change-point analysis,

Reference 44

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Observation 31dc8061-41ed-45d8-8b4d-663044650253 · outbound

This paper cites Practical and powerful kernel-based change-point detection,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Practical and powerful kernel-based change-point detection,

Reference 45

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Observation 08060b78-6cb3-42cb-8047-70537414674d · outbound

This paper cites Learning under concept drift: A review,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Learning under concept drift: A review,

Reference 46

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Observation 1f000190-480d-4fa4-b34c-33a929027175 · outbound

This paper cites Learning with drift detection,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Learning with drift detection,

Reference 47

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Observation 8d00e0fe-82c5-4ddf-a6a3-988d6fc450f5 · outbound

This paper cites Concept drift detection for deep learning aided receivers in dynamic channels,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Concept drift detection for deep learning aided receivers in dynamic channels,

Reference 48

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Observation 4c5ebe03-baf3-4849-bc30-5056cfe086fe · outbound

This paper cites Adversarial learning targeting deep neural network classification: A comprehensive review of defenses against attacks,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Adversarial learning targeting deep neural network classification: A comprehensive review of defenses against attacks,

Reference 49

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Observation 107bcef4-4ea2-40f5-b692-69df8265f4bc · outbound

This paper cites Unsupervised learned Kalman filtering,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Unsupervised learned Kalman filtering,

Reference 50

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Observation dc207489-d11b-42f2-a239-acd35b227845 · outbound

This paper cites Training recurrent neural networks,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Training recurrent neural networks,

Reference 51

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Observation bcf1682e-69b2-45e4-a80e-7cca8589a686 · outbound

This paper cites Memory-efficient backpropagation through time,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Memory-efficient backpropagation through time,

Reference 52

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Observation 651494cb-4080-49a9-aee3-e4533cb49e94 · outbound

This paper cites Uncertainty quantification in deep learning based Kalman filters,.

Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection Uncertainty quantification in deep learning based Kalman filters,

Reference 53

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source=pdf_text observed=2026-08-02T05:24:23.028428Z digest=sha256:b437b864b55b7dbffbdb8f5e19907b7d28df3d2017b64047b309c9e087adf9b1

Pith citing papers

Observation 338cbcc9-cf90-4a1b-81d4-9aa708e101a8 · inbound

ARC: Augmented-Rank Conformalization for Changepoint Localization --- Finite-Sample Validity and Distribution-Robust Efficiency cites this paper.

ARC: Augmented-Rank Conformalization for Changepoint Localization --- Finite-Sample Validity and Distribution-Robust Efficiency Change-Aware Self-Adaptive AI-Aided Kalman Filters With Neural Change Point Detection

Reference 41

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source=pdf_text observed=2026-08-14T04:44:23.868636Z digest=sha256:5f1892e95c0f8c6a379d002fbaedaf74373b52f9ce2c1dd0e2690987de91c6d0