Pith. sign in

Paper Citation Record · LEDGER

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations

As of 17 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 1 inbound Pith citation observation for arXiv:2411.13917.

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

pith.paper-citation-record.v1
2411.13917 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:48:47.855677Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-19T21:45:52.558668Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T21:47:48.420285Z

Reference resolution

30 of 30 outbound references displayed

  • verified exact0
  • verified fuzzy15
  • unresolved15
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a943369d-1e46-4942-8196-c274fd00c93b · outbound

This paper cites Context-dependent sentiment analysis in user-generated videos[C]//Proceedings of the 55th annual meeting of the association for computational linguistics (volume 1: Long papers).

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations Context-dependent sentiment analysis in user-generated videos[C]//Proceedings of the 55th annual meeting of the association for computational linguistics (volume 1: Long papers)

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:48:50.012219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T15:48:46.841671Z digest=sha256:da9756434348285a33eaf7080f82120d1ac0e0c4599f7cec3e86a6b60ac0b74d

Observation b704bb25-ef76-46d7-8c37-479cdb1d963f · outbound

This paper cites DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in Conversation.

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in Conversation

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-12T15:48:47.046602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:48:47.046602Z digest=sha256:e0b2f6eaafad574381163a5114aef19a2e9fab3f3120fdbe8bb2a56b4c047f9d

Observation 2357c354-2826-4f9b-aa7a-8e8644782ee1 · outbound

This paper cites An iterative emotion interaction network for emotion recognition in conversations[C]//Proceedings of the 28th international conference on computational linguistics.

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations An iterative emotion interaction network for emotion recognition in conversations[C]//Proceedings of the 28th international conference on computational linguistics

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:48:49.684719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T15:48:47.075695Z digest=sha256:a09dc92b82ba62ec6650bb967b04ccf668adc9f2c6fee958ed59f5f4c8840412

Observation 356f9cc1-05e6-4989-91e8-c8998e1fca25 · outbound

This paper cites Contextualized emotion recognition in conversation as sequence tagging[C]//Proceedings of the 21th annual meeting of the special interest group on discourse and dialogue.

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations Contextualized emotion recognition in conversation as sequence tagging[C]//Proceedings of the 21th annual meeting of the special interest group on discourse and dialogue

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:48:49.644632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T15:48:47.083300Z digest=sha256:da339f12a539e76c6ab545a0c7eb10574c866074eb32ca960daf054120ba823e

Observation 74cdb885-2e80-4a0a-a739-704dd8a8555f · outbound

This paper cites an unresolved cited work.

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-12T15:48:49.598852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T15:48:47.090402Z digest=sha256:6873a949a58f51597e295cfe888815c90e1a239e44fb9e29d6be7421b0f971e7

Observation 5391975e-4c0b-4a2e-812b-4ee4c390715c · outbound

This paper cites Quantum-inspired neural network for conversational emotion recognition[C]//Proceedings of the AAAI Conference on Artificial Intelligence.

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations Quantum-inspired neural network for conversational emotion recognition[C]//Proceedings of the AAAI Conference on Artificial Intelligence

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:48:49.474600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T15:48:47.109189Z digest=sha256:5af300de538aa9a330ffb1420ae05bebfcf4dea6be32f080fd47140924bc95d2

Observation d0073380-1812-4d6c-b59a-9be09bf8aa44 · outbound

This paper cites MMGCN: Multimodal Fusion via Deep Graph Convolution Network for Emotion Recognition in Conversation.

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations MMGCN: Multimodal Fusion via Deep Graph Convolution Network for Emotion Recognition in Conversation

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-12T15:48:47.122557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:48:47.122557Z digest=sha256:73d515242ec63fa9d80401ec778785d13c1d331946e47ee1ce7482eb72505d89

Observation dc7804b0-8dae-49e8-bb2c-11e790df5add · outbound

This paper cites A multi-view network for real-time emotion recognition in conversations[J].

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations A multi-view network for real-time emotion recognition in conversations[J]

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:48:49.274546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T15:48:47.143590Z digest=sha256:d32010b40db81f8e76a8a1f200626b8180b13b473e259af6d1ed018f47685bef

Observation 4766a35a-5b35-4f58-9c2e-9772eb619698 · outbound

This paper cites an unresolved cited work.

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations Unresolved cited work

Reference 10

Resolution
unresolved
raw_fallback, observed 2026-08-12T15:48:49.192436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T15:48:47.237587Z digest=sha256:6796510c61a6907bedc0523b0f90b4cbcc17a5bf49050dacb55228b68c12d335

Observation 8402a3f6-fe4d-4719-9f7e-f5a849bad33a · outbound

This paper cites an unresolved cited work.

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations Unresolved cited work

Reference 11

Resolution
unresolved
raw_fallback, observed 2026-08-12T15:48:49.130128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T15:48:47.293247Z digest=sha256:283111278e32e9471032301f7b6c2302f75d50534522b114b84c5344bb6b5963

Observation 6a8e0dc3-79d8-4790-821a-2c063a66d75e · outbound

This paper cites GA2MIF: graph and attention based two-stage multi-source information fusion for conversational emotion detection[J].

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations GA2MIF: graph and attention based two-stage multi-source information fusion for conversational emotion detection[J]

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:48:49.099567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T15:48:47.348470Z digest=sha256:1e5cd0e493ae1e04730ec652308e95de8c03f9cc49dcb004e380807d8f0cd598

Observation 3dd10dca-c75a-43b3-acd6-b5f5325af77c · outbound

This paper cites Dynamic emotion modeling with learn- able graphs and graph inception network[J].

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations Dynamic emotion modeling with learn- able graphs and graph inception network[J]

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:48:49.028811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T15:48:47.382589Z digest=sha256:79b90e202a82aead7f71a8b628227116395ded30de37f6b636984c771bc157ae

Observation 117b44a6-7114-47bd-aef9-5a72784e57a4 · outbound

This paper cites DEEPTalk: Dynamic Emotion Embedding for Probabilistic Speech-Driven 3D Face Animation.

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations DEEPTalk: Dynamic Emotion Embedding for Probabilistic Speech-Driven 3D Face Animation

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-12T15:48:47.392309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:48:47.392309Z digest=sha256:89764627756270aab1e1667e431a242518f9d58964e5a4a24694d225fc74ac3a

Observation 04c867fd-a645-4191-928a-aaac764e64d0 · outbound

This paper cites Spiking neural networks[J].

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations Spiking neural networks[J]

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:48:49.001219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T15:48:47.409485Z digest=sha256:4d4bc949c4ae6a9f8f6c28542da6b0b4224676af8d9d8aceaa042aea56692a57

Observation fb30cf66-fb1e-4286-bcd4-a4a6a749e7bd · outbound

This paper cites Spikformer: When Spiking Neural Network Meets Transformer.

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations Spikformer: When Spiking Neural Network Meets Transformer

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-12T15:48:47.421319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:48:47.421319Z digest=sha256:130d9daa3a75a6f349162aa511da4591978cddde3fd2c828e2d3095ae290b122

Observation 2c617e25-54c9-4c4b-a395-45e3799d6d5a · outbound

This paper cites Spikformer V2: Join the High Accuracy Club on ImageNet with an SNN Ticket.

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations Spikformer V2: Join the High Accuracy Club on ImageNet with an SNN Ticket

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-12T15:48:47.430752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:48:47.430752Z digest=sha256:65e120e56b52309bc3b8ff44626e36474da2b55d32349abbcda18307d349a423

Observation 71f6a02a-5588-4675-a436-3c090e793f67 · outbound

This paper cites MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations.

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-12T15:48:47.444332Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:48:47.444332Z digest=sha256:541e35a6343e0ce8aefa721fe24edd2f868922b2dac21e10a60cb1eb72325c1c

Observation 56ca7f3a-db8c-4e79-a04d-775c7b8ae52d · outbound

This paper cites IEMOCAP: Interactive emotional dyadic motion capture database[J].

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations IEMOCAP: Interactive emotional dyadic motion capture database[J]

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-12T15:48:47.494089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:48:47.494089Z digest=sha256:a595661b825b60be95d7db0127f687b2a9e913417be04014985f654c0edaf550

Observation 4e47ccd1-bfb3-4a27-9c06-e7797b82aaee · outbound

This paper cites An efficient approach to informative feature extraction from multimodal data[C]//Proceedings of the AAAI Conference on Artificial Intelligence.

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations An efficient approach to informative feature extraction from multimodal data[C]//Proceedings of the AAAI Conference on Artificial Intelligence

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:48:48.852464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T15:48:47.532105Z digest=sha256:5a0f48dbfba711e1d1dab132c6d0405cc34ac399fb5b02272a3c49b27774757e

Observation 56cdd775-53a1-4b4f-884d-8aa46e3736eb · outbound

This paper cites An efficient approach for audio-visual emo- tion recognition with missing labels and missing modalities[C]//2021 IEEE international conference on multimedia and Expo (ICME).

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations An efficient approach for audio-visual emo- tion recognition with missing labels and missing modalities[C]//2021 IEEE international conference on multimedia and Expo (ICME)

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:48:48.719899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T15:48:47.587302Z digest=sha256:19fcfbf21104601948c0e6589cab9589a3320432131d4144f6a8aadc58d19de8

Observation 594e79e0-6fb2-4a6b-a019-268ec9712253 · outbound

This paper cites Dice Loss for Data-imbalanced NLP Tasks.

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations Dice Loss for Data-imbalanced NLP Tasks

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-12T15:48:47.598407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:48:47.598407Z digest=sha256:729fdd19206f752373947e51140f4a6d32c1064700525f105a24ef0821a4f52d

Observation 72d41727-a899-47cf-88c0-ab14a1dd42ce · outbound

This paper cites Focal loss for dense object detec- tion[C]//Proceedings of the IEEE international conference on computer vision.

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations Focal loss for dense object detec- tion[C]//Proceedings of the IEEE international conference on computer vision

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:48:48.669132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T15:48:47.617619Z digest=sha256:004f376f2b301b275f303a43ef944c9cda3d41893517780b829b20f211b38817

Observation 35cddb80-fbe7-48d0-a0c9-e27a45a1f58e · outbound

This paper cites Deep long-tailed learning: A survey[J].

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations Deep long-tailed learning: A survey[J]

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:48:48.632446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T15:48:47.632221Z digest=sha256:4527f938bc6a09f70c287e9ddfec84c6272698fd0210671dcb8c0768b9369437

Observation f0b0b0aa-0cf6-42d1-96ca-f047f6f7cf1c · outbound

This paper cites Distribution alignment: A unified frame- work for long-tail visual recognition[C]//Proceedings of the IEEE/CVF conference on computer vision and pattern recognition.

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations Distribution alignment: A unified frame- work for long-tail visual recognition[C]//Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:48:48.580326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T15:48:47.647393Z digest=sha256:424a12668ed62714231ad77eef7a2c9ba48e83b54ac4a9692bf9abfb42f35e76

Observation 71ea3ada-cfa0-4b7d-b2b0-2d1e78574ad8 · outbound

This paper cites Balancing Methods for Multi-label Text Classification with Long-Tailed Class Distribution.

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations Balancing Methods for Multi-label Text Classification with Long-Tailed Class Distribution

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-12T15:48:47.717366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:48:47.717366Z digest=sha256:40f452894fece7fd6acbf5ca53dfe38f01dd892e08f383f6a0606cdb8935eeff

Observation b2bf87ad-9c2c-43c5-974a-23c178353c98 · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-12T15:48:47.759507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:48:47.759507Z digest=sha256:5ddec0a0edb2eb65efe9dfa04b95f6568d3dedf48660a3d5b5e77a65cd585982

Observation 6c7225c0-4c51-4d33-8471-4c346c44e765 · outbound

This paper cites Opensmile: the munich versatile and fast open-source audio feature extractor[C]//Proceedings of the 18th ACM international conference on Multimedia.

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations Opensmile: the munich versatile and fast open-source audio feature extractor[C]//Proceedings of the 18th ACM international conference on Multimedia

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:48:48.527025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T15:48:47.792356Z digest=sha256:0f9d4ca50204a1ff87796c21fc6acf2624adf83b872ecaa311fb73df2b96679a

Observation f4273c5c-6d3d-4c7b-9b11-a2293c9e5550 · outbound

This paper cites Dialoguernn: An attentive rnn for emotion detection in conversations[C]//Proceedings of the AAAI conference on artificial intelligence.

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations Dialoguernn: An attentive rnn for emotion detection in conversations[C]//Proceedings of the AAAI conference on artificial intelligence

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T15:48:49.963675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T15:48:47.820224Z digest=sha256:0093fcf20d07b5d65b30bd7e54ac1ed815697051e0e823eae801dbe3d9ba5ec3

Observation 40723e38-41f0-41e3-b5b5-4176f1059dcc · outbound

This paper cites InstructERC: Reforming Emotion Recognition in Conversation with Multi-task Retrieval-Augmented Large Language Models.

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations InstructERC: Reforming Emotion Recognition in Conversation with Multi-task Retrieval-Augmented Large Language Models

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-12T15:48:47.849733Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:48:47.849733Z digest=sha256:5c76db6667a5210f3d7a2f988a0fa2a1530ea87d46d9169b5624b00649fb415d

Observation 80bb6f9b-fff9-41a5-903f-c14c64a8430b · outbound

This paper cites Fake Artificial Intelligence Generated Contents (FAIGC): A Survey of Theories, Detection Methods, and Opportunities.

SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations Fake Artificial Intelligence Generated Contents (FAIGC): A Survey of Theories, Detection Methods, and Opportunities

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-12T15:48:47.855677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:48:47.855677Z digest=sha256:0af3b09954554dc8f10f188f50139dffb2272a8441c59754f7ecd47be0e884cd

Pith citing papers

Observation d0ef82cb-a11d-4017-a6ac-77a957611cd6 · inbound

Controlling Decision Drift in Multimodal Sentiment Analysis with Missing Modalities cites this paper.

Controlling Decision Drift in Multimodal Sentiment Analysis with Missing Modalities SpikEmo: Enhancing Emotion Recognition With Spiking Temporal Dynamics in Conversations

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-19T21:47:48.422281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-19T21:45:52.558668Z digest=sha256:a116e1d9969082ce63dac9040fc8a70b6a85cc7f5477aae65e10b293faac96eb