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Paper Citation Record · LEDGER

Evaluation of Seismic Artificial Intelligence with Uncertainty

As of 15 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 0 inbound Pith citation observations for arXiv:2501.14809.

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

pith.paper-citation-record.v1
2501.14809 v2

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:17:39.777500Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

53 of 53 outbound references displayed

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  • unresolved15
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 01afd068-2efb-4150-b315-314611c3b1b3 · outbound

This paper cites PhaseNet: A Deep-Neural-Network-Based Seismic Arrival Time Picking Method.Geophys.

Evaluation of Seismic Artificial Intelligence with Uncertainty PhaseNet: A Deep-Neural-Network-Based Seismic Arrival Time Picking Method.Geophys

Reference 1

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Source-reported events for the cited work

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Observation 107ed74d-f000-4644-875b-10eceeb84c6f · outbound

This paper cites an unresolved cited work.

Evaluation of Seismic Artificial Intelligence with Uncertainty Unresolved cited work

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 6f3c3d36-777d-4795-ace2-bef77360d25c · outbound

This paper cites Deep Learning for Geophysics: Current and Future Trends.Rev.

Evaluation of Seismic Artificial Intelligence with Uncertainty Deep Learning for Geophysics: Current and Future Trends.Rev

Reference 3

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation defe717e-371f-467f-abb7-772c4e6adad2 · outbound

This paper cites Mostafa Mousavi and Gregory C.

Evaluation of Seismic Artificial Intelligence with Uncertainty Mostafa Mousavi and Gregory C

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation afceb528-80b3-4f7b-bf85-7974d8d845ec · outbound

This paper cites Mostafa Mousavi, Gregory C.

Evaluation of Seismic Artificial Intelligence with Uncertainty Mostafa Mousavi, Gregory C

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 2c324bd0-1315-44e7-8b80-f670805149cf · outbound

This paper cites SeisBench—A Toolbox for Machine Learning in Seismology.Seismol.

Evaluation of Seismic Artificial Intelligence with Uncertainty SeisBench—A Toolbox for Machine Learning in Seismology.Seismol

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 8ebe9240-1fdd-45ca-8a57-62cc76992aaf · outbound

This paper cites Which Picker Fits My Data? A Quantitative Evaluation of Deep Learning Based Seismic Pickers.J.

Evaluation of Seismic Artificial Intelligence with Uncertainty Which Picker Fits My Data? A Quantitative Evaluation of Deep Learning Based Seismic Pickers.J

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 25c2326e-a62e-46c6-89d6-5a417d38de96 · outbound

This paper cites Accounting for Variance in Machine Learning Benchmarks.

Evaluation of Seismic Artificial Intelligence with Uncertainty Accounting for Variance in Machine Learning Benchmarks

Reference 8

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Source-reported events for the cited work

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Observation 07fa7b00-6f76-410b-8c89-3960196e1b94 · outbound

This paper cites Reporting Score Distributions Makes a Difference: Performance Study of LSTM-networks for Sequence Tagging.

Evaluation of Seismic Artificial Intelligence with Uncertainty Reporting Score Distributions Makes a Difference: Performance Study of LSTM-networks for Sequence Tagging

Reference 9

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation f9ef68d1-b719-4563-9753-229b56ce3f7b · outbound

This paper cites Spiegelhalter.

Evaluation of Seismic Artificial Intelligence with Uncertainty Spiegelhalter

Reference 10

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 786c0fc3-aed2-46f8-9a44-545af65e8d65 · outbound

This paper cites Dietterich.

Evaluation of Seismic Artificial Intelligence with Uncertainty Dietterich

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation d2692658-8357-4372-911a-332704357bf8 · outbound

This paper cites The Benchmark Lottery.

Evaluation of Seismic Artificial Intelligence with Uncertainty The Benchmark Lottery

Reference 12

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Source-reported events for the cited work

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Observation af8f9101-c173-4b20-9cf1-884cde7bc7e9 · outbound

This paper cites Follow the leader(board) with confidence: Estimating p-values from a single test set with item and response variance.

Evaluation of Seismic Artificial Intelligence with Uncertainty Follow the leader(board) with confidence: Estimating p-values from a single test set with item and response variance

Reference 13

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 9c4ef5c7-81c5-4590-b8d4-e164479232a7 · outbound

This paper cites Measuring the Data Efficiency of Deep Learning Methods.

Evaluation of Seismic Artificial Intelligence with Uncertainty Measuring the Data Efficiency of Deep Learning Methods

Reference 14

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Source-reported events for the cited work

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Observation 7ed52728-abd0-478b-83c0-050462b8b889 · outbound

This paper cites an unresolved cited work.

Evaluation of Seismic Artificial Intelligence with Uncertainty Unresolved cited work

Reference 15

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 97a3e525-4f2b-44b5-b446-b7c5a8529ccf · outbound

This paper cites Bornstein, D.

Evaluation of Seismic Artificial Intelligence with Uncertainty Bornstein, D

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 7c07914a-a7f4-43ac-a053-9836d8fbc38c · outbound

This paper cites SpanSeq: similarity-based sequence data splitting method for improved development and assessment of deep learning projects.NAR Genomics Bioinf., 6(3):lqae106, July 2024.

Evaluation of Seismic Artificial Intelligence with Uncertainty SpanSeq: similarity-based sequence data splitting method for improved development and assessment of deep learning projects.NAR Genomics Bioinf., 6(3):lqae106, July 2024

Reference 17

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 7c49e46a-b7f0-4e4e-9d52-9c3c0d00ccaa · outbound

This paper cites Ross, Men-Andrin Meier, Egill Hauksson, and Thomas H.

Evaluation of Seismic Artificial Intelligence with Uncertainty Ross, Men-Andrin Meier, Egill Hauksson, and Thomas H

Reference 18

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 7ba00d09-9798-4a0d-9a8b-8d2ae43d576f · outbound

This paper cites Mostafa Mousavi, William L.

Evaluation of Seismic Artificial Intelligence with Uncertainty Mostafa Mousavi, William L

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 536dbeeb-10a3-4ec2-9030-745d1f98489c · outbound

This paper cites CubeNet: Array-Based Seismic Phase Picking with Deep Learning.Seismol.

Evaluation of Seismic Artificial Intelligence with Uncertainty CubeNet: Array-Based Seismic Phase Picking with Deep Learning.Seismol

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 2b7d417d-a12d-433a-af2a-5f66f24bc23a · outbound

This paper cites Deep learning for seismic phase detection and picking in the aftershock zone of 2008 M7.9 Wenchuan Earthquake.

Evaluation of Seismic Artificial Intelligence with Uncertainty Deep learning for seismic phase detection and picking in the aftershock zone of 2008 M7.9 Wenchuan Earthquake

Reference 21

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 78781a80-91dd-4901-aafa-39a8fba620c8 · outbound

This paper cites Mostafa Mousavi, Peter Bailis, and Gregory C.

Evaluation of Seismic Artificial Intelligence with Uncertainty Mostafa Mousavi, Peter Bailis, and Gregory C

Reference 22

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 1f0cfb48-04ef-4653-b660-2c187f4f77c9 · outbound

This paper cites Seismic-phase detection using multiple deep learning models for global and local representations of waveforms.Geophys.

Evaluation of Seismic Artificial Intelligence with Uncertainty Seismic-phase detection using multiple deep learning models for global and local representations of waveforms.Geophys

Reference 23

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation d361cb96-e6bf-4270-b857-d32046c77f89 · outbound

This paper cites OBSTransformer: a deep-learning seismic phase picker for OBS data using automated labelling and transfer learning.Geophys.

Evaluation of Seismic Artificial Intelligence with Uncertainty OBSTransformer: a deep-learning seismic phase picker for OBS data using automated labelling and transfer learning.Geophys

Reference 24

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 513b0c1a-7a36-4d93-a94b-64e93f6a126f · outbound

This paper cites Cianetti, R.

Evaluation of Seismic Artificial Intelligence with Uncertainty Cianetti, R

Reference 25

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 44f56710-a2cc-4e24-8a2a-cc6e3c1ca786 · outbound

This paper cites Beroza, and William L.

Evaluation of Seismic Artificial Intelligence with Uncertainty Beroza, and William L

Reference 26

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation fbe04f29-8dc4-4674-a76a-849b3cb86b07 · outbound

This paper cites Yoon, Elizabeth S.

Evaluation of Seismic Artificial Intelligence with Uncertainty Yoon, Elizabeth S

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 10e26ce4-3d0f-4f6b-9eb2-de74d926ec16 · outbound

This paper cites Armstrong, Zachary Claerhout, Ben Baker, and Keith D.

Evaluation of Seismic Artificial Intelligence with Uncertainty Armstrong, Zachary Claerhout, Ben Baker, and Keith D

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 56096bd7-5ba4-41ce-b0cb-113cf6ea60f6 · outbound

This paper cites Mostafa Mousavi, Yixiao Sheng, Weiqiang Zhu, and Gregory C.

Evaluation of Seismic Artificial Intelligence with Uncertainty Mostafa Mousavi, Yixiao Sheng, Weiqiang Zhu, and Gregory C

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation cc6876b3-69ce-4901-ba75-6d15bcbe7774 · outbound

This paper cites INSTANCE – the Italian seismic dataset for machine learning.Earth Syst.

Evaluation of Seismic Artificial Intelligence with Uncertainty INSTANCE – the Italian seismic dataset for machine learning.Earth Syst

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation ecf7809e-9ee7-42ae-9a38-dd8a1bec7de2 · outbound

This paper cites Scikit-learn: Machine Learning in Python.

Evaluation of Seismic Artificial Intelligence with Uncertainty Scikit-learn: Machine Learning in Python

Reference 31

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:17:39.648503Z digest=sha256:9c7a12564b5da15ff4faed5bd316a2dc6e28fc61d97107aab140794f707bd113

Observation cb5a59a4-668e-4772-a7b0-ee5d4033f8bc · outbound

This paper cites Development of a high-performance seismic phase picker using deep learning in the Hakone volcanic area.Earth Planets Space, 75(1):85, May 2023.

Evaluation of Seismic Artificial Intelligence with Uncertainty Development of a high-performance seismic phase picker using deep learning in the Hakone volcanic area.Earth Planets Space, 75(1):85, May 2023

Reference 32

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation ce906589-4ca2-4248-927e-75dbd16fde37 · outbound

This paper cites U-Net: Convolutional Networks for Biomedical Image Segmentation.

Evaluation of Seismic Artificial Intelligence with Uncertainty U-Net: Convolutional Networks for Biomedical Image Segmentation

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 2ad18461-135a-4762-bbf4-54e7cf2d2b5c · outbound

This paper cites Chamberlain, John Townend, and Emily Warren-Smith.

Evaluation of Seismic Artificial Intelligence with Uncertainty Chamberlain, John Townend, and Emily Warren-Smith

Reference 34

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raw_fallback, observed 2026-08-10T20:17:40.154018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 9857ff94-4064-400e-8df4-ddbf23fb9f9d · outbound

This paper cites Delbridge, and David R.

Evaluation of Seismic Artificial Intelligence with Uncertainty Delbridge, and David R

Reference 35

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verified fuzzy
raw_fallback, observed 2026-08-10T20:17:40.141748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:17:39.665801Z digest=sha256:58efbc4c4079cbc660924ee0c06882cd1abd06b04d67758b0b4c6bd4489ca5e1

Observation 1daa3db9-3f2d-47fc-a356-12f22c1a7280 · outbound

This paper cites Santos-Villalobos, Singanallur V.

Evaluation of Seismic Artificial Intelligence with Uncertainty Santos-Villalobos, Singanallur V

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-10T20:17:40.126608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:17:39.672387Z digest=sha256:47bca18a9920539742e5f724a514acd0ff46ba222f9d9b488db6d919ccd01f4e

Observation 4e734540-69a6-4c59-8f0e-fdb2eaca663c · outbound

This paper cites Fine-Tuning U-Net for Ultrasound Image Segmentation: Different Layers, Different Outcomes.IEEE Trans.

Evaluation of Seismic Artificial Intelligence with Uncertainty Fine-Tuning U-Net for Ultrasound Image Segmentation: Different Layers, Different Outcomes.IEEE Trans

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:17:40.113354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:17:39.678269Z digest=sha256:3387670d262360526c9d59c4da4f3c3ddcd53f8f39c652b9725c141532868706

Observation b963a732-29be-4c57-835f-5d627d534034 · outbound

This paper cites Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles.

Evaluation of Seismic Artificial Intelligence with Uncertainty Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles

Reference 38

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no resolver link, observed 2026-08-10T20:17:39.683466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:17:39.683466Z digest=sha256:0c07af7b402d56fb45bff1eaa573cd7230a75596a70814f30a91ea335c7051c4

Observation b061ebb9-b5cb-4ca3-af9a-27c3f9011461 · outbound

This paper cites Snapshot Ensembles: Train 1, get M for free.

Evaluation of Seismic Artificial Intelligence with Uncertainty Snapshot Ensembles: Train 1, get M for free

Reference 39

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no resolver link, observed 2026-08-10T20:17:39.689902Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:17:39.689902Z digest=sha256:231aa1e65330c2b7eee529549b4a75d5ec686ff4617db39d9aad06b2921c6b42

Observation 849e2e1b-29ba-4225-987c-9f9b4b36ccbf · outbound

This paper cites Ganaie, Minghui Hu, A.K.

Evaluation of Seismic Artificial Intelligence with Uncertainty Ganaie, Minghui Hu, A.K

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:17:40.097426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:17:39.697981Z digest=sha256:6afce0c1fba4a605b2c340ec330772c77934ee1efdfc2b887f50a2f4b17808a8

Observation 2ca7e421-5b7a-4498-ab1a-31729767c729 · outbound

This paper cites PyTorch: An Imperative Style, High-Performance Deep Learning Library.

Evaluation of Seismic Artificial Intelligence with Uncertainty PyTorch: An Imperative Style, High-Performance Deep Learning Library

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-10T20:17:39.706453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:17:39.706453Z digest=sha256:0f513a6cc8976b8bb7a16fada9d11ea882ac2b65a467bbbca929121b3c84da18

Observation c077f657-226c-4f0a-a51f-8e07fdfb2bf5 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Evaluation of Seismic Artificial Intelligence with Uncertainty Adam: A Method for Stochastic Optimization

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-10T20:17:39.711545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:17:39.711545Z digest=sha256:0869c5f4a0bce2c0f9bc1cdd566d92b3a6c0a69c541900eb427c59447737ca66

Observation d2f39f54-2a49-4298-bb14-63c7156e7e8b · outbound

This paper cites Benchmark on the accuracy and efficiency of several neural network based phase pickers using datasets from China Seismic Network.Earthquake Sci., 36(2):113–131, April 2023.

Evaluation of Seismic Artificial Intelligence with Uncertainty Benchmark on the accuracy and efficiency of several neural network based phase pickers using datasets from China Seismic Network.Earthquake Sci., 36(2):113–131, April 2023

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:17:40.081563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:17:39.717762Z digest=sha256:6e8078a6d51041791056beb798dae3c8246da8738d9775ad1f69613e14769227

Observation 63100ad8-9697-48ae-96b9-102ee16be536 · outbound

This paper cites Bayesian approach for neural networks—review and case studies.Neural Networks, 14(3):257–274, April 2001.

Evaluation of Seismic Artificial Intelligence with Uncertainty Bayesian approach for neural networks—review and case studies.Neural Networks, 14(3):257–274, April 2001

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:17:40.065740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:17:39.724491Z digest=sha256:3070a8f01d3cdbef974a4529d8f7b3f1c1117ce9f939a8c637d339d1a0b36503

Observation aca87697-daa3-4e10-ae84-903b1db4a39f · outbound

This paper cites Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning.

Evaluation of Seismic Artificial Intelligence with Uncertainty Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-10T20:17:39.730030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:17:39.730030Z digest=sha256:e889318ce85e12c5f72cba7cc6f6e6c3a11c0a6255348b2407057f8cbce10054

Observation 9f43cd9c-e95a-41a9-92cb-ad2049b3738b · outbound

This paper cites A Simple Baseline for Bayesian Uncertainty in Deep Learning.

Evaluation of Seismic Artificial Intelligence with Uncertainty A Simple Baseline for Bayesian Uncertainty in Deep Learning

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-10T20:17:39.734955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:17:39.734955Z digest=sha256:2387b3ebd71d0273892eb64111e62a08c0f293c8281134de3a626d5810d926c1

Observation dfdf93ef-382c-4e32-be81-66ebcca63525 · outbound

This paper cites A Survey of Uncertainty in Deep Neural Networks.

Evaluation of Seismic Artificial Intelligence with Uncertainty A Survey of Uncertainty in Deep Neural Networks

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-10T20:17:39.740946Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:17:39.740946Z digest=sha256:93e0dca1ac6338af760208043d0249cbb831ba40af14a49afedddd9c9f560602

Observation 176ebc66-5dd5-48c8-bd58-fae654510ebb · outbound

This paper cites Bayesian Deep Learning and a Probabilistic Perspective of Generalization.

Evaluation of Seismic Artificial Intelligence with Uncertainty Bayesian Deep Learning and a Probabilistic Perspective of Generalization

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-10T20:17:39.747447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:17:39.747447Z digest=sha256:b49c70a125a95fc339a918f4baa620807875fb09323d12c2d583b3bdcf26bf94

Observation a0cd3de4-f3fb-497a-9217-af21f0e49ae0 · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

Evaluation of Seismic Artificial Intelligence with Uncertainty On the Opportunities and Risks of Foundation Models

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-10T20:17:39.752216Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:17:39.752216Z digest=sha256:5796f435a5338474fe0f7d1fc22a769fc380c75214a9df57b9e24ac69d718e4c

Observation 5f3f6625-76fa-4d6f-b2f0-d157b38065db · outbound

This paper cites Seismic foundation model: A next generation deep-learning model in geophysics.Geophysics, 90(2):IM59–IM79, March 2025.

Evaluation of Seismic Artificial Intelligence with Uncertainty Seismic foundation model: A next generation deep-learning model in geophysics.Geophysics, 90(2):IM59–IM79, March 2025

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:17:40.050215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:17:39.757997Z digest=sha256:ac29984b4683bc7d42a7f1b418f25fdb4628fee6655f598671ada21b9ed5b5c9

Observation c11548c7-67de-48b2-b551-60ab706c0b71 · outbound

This paper cites A foundation model enpowered by a multi-modal prompt engine for universal seismic geobody interpretation across surveys, September.

Evaluation of Seismic Artificial Intelligence with Uncertainty A foundation model enpowered by a multi-modal prompt engine for universal seismic geobody interpretation across surveys, September

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:17:40.036166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:17:39.766662Z digest=sha256:87892bb24cc050eb8bdb4c5d67f49d057882d0703ba64eb289051e4ab1055552

Observation ac8234cb-8c75-4d7d-b35d-405621b38159 · outbound

This paper cites SeisLM: a Foundation Model for Seismic Waveforms.

Evaluation of Seismic Artificial Intelligence with Uncertainty SeisLM: a Foundation Model for Seismic Waveforms

Reference 52

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unresolved
no resolver link, observed 2026-08-10T20:17:39.772428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:17:39.772428Z digest=sha256:9f202928e53fa0d2a991f5c382769f5c4eafa67a35bd4e812e8726d7e3a8372d

Observation a565e4f0-c24c-49b3-ac03-dbb3c16ae0dc · outbound

This paper cites SeisCLIP: A Seismology Foundation Model Pre-Trained by Multimodal Data for Multipurpose Seismic Feature Extraction.IEEE Trans.

Evaluation of Seismic Artificial Intelligence with Uncertainty SeisCLIP: A Seismology Foundation Model Pre-Trained by Multimodal Data for Multipurpose Seismic Feature Extraction.IEEE Trans

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:17:40.022040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T20:17:39.777500Z digest=sha256:63b16883ad0532fa2256736093629febe221fa77ef9a4643402d6b434872fcb0

Pith citing papers

No inbound Pith citation observations are available.