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Paper Citation Record · LEDGER

A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction

As of 11 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:2506.18018.

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

pith.paper-citation-record.v1
2506.18018 v1

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:28:03.616671Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

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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

51 of 51 outbound references displayed

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External citation measurements

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Outbound references

Observation f5977860-27c3-402c-9857-30589e461582 · outbound

This paper cites S., Fnais, M., Giannadaki, D.

A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction S., Fnais, M., Giannadaki, D

Reference 1

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Observation 04c78664-fb14-401c-8ac4-2192532b1d44 · outbound

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A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction & Unger, N

Reference 2

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A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction Unresolved cited work

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A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction Unresolved cited work

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A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction Unresolved cited work

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A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction Unresolved cited work

Reference 7

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A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction Unresolved cited work

Reference 8

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Observation 6933e581-6b4c-4a99-83a5-8e47de06fa3a · outbound

This paper cites J., Santillana, M., Wang, X.

A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction J., Santillana, M., Wang, X

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Observation 14ddc2d5-c302-4a65-955c-0a06610a81db · outbound

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A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction Unresolved cited work

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A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction & Huang, X.-F

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A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction X., Jang, C., Zhu, Y

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A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction W., Hill, J

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A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction Superhuman Accuracy on the SNEMI3D Connectomics Challenge

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A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction The distribution of points in a cube and the accurate evaluation of integrals (in Russian) Zh

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A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction Solving Partial Differential Equations with Point Source Based on Physics-Informed Neural Networks

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation f5e2336b-9c70-41f7-be59-5b82a5f6c7db · outbound

This paper cites an unresolved cited work.

A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction Unresolved cited work

Reference 38

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:28:07.466440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation af8cbcd0-6dc4-4869-aef8-c8b78b1292b7 · outbound

This paper cites an unresolved cited work.

A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction Unresolved cited work

Reference 39

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:28:07.245137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 8e8d2329-f2d5-4930-b3e8-827cfcabdde2 · outbound

This paper cites & Mauzerall, D.

A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction & Mauzerall, D

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:28:07.078251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 29d1cab9-8ee7-4291-9284-6a2d2bc22c44 · outbound

This paper cites an unresolved cited work.

A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction Unresolved cited work

Reference 41

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:28:06.917706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 79529fde-a892-4cba-a74b-1d50bd2a6999 · outbound

This paper cites an unresolved cited work.

A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction Unresolved cited work

Reference 42

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:28:06.689637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 96a6ffa5-7ed7-4bec-adca-5f9188a89e14 · outbound

This paper cites an unresolved cited work.

A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction Unresolved cited work

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:28:06.521926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 786bc3e8-8405-4cd2-a7a0-f4331e7abb58 · outbound

This paper cites an unresolved cited work.

A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction Unresolved cited work

Reference 44

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:28:06.214745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T23:28:02.817044Z digest=sha256:59cc887b324efaf081e8fe2a02e971d4812a8f0cdc8267a441ba08c5d54dcd2d

Observation 45a1ccb0-d7a4-421e-8854-395f2c9096a6 · outbound

This paper cites an unresolved cited work.

A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction Unresolved cited work

Reference 45

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:28:06.008677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T23:28:02.926613Z digest=sha256:cc90796953f1fc743a97b392cda588d5c55d2d210183edbd4f9e1831afc98dae

Observation f63c5061-16d5-47e4-86c4-ed55dbfd3477 · outbound

This paper cites & Henze, G.

A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction & Henze, G

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:28:05.789655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T23:28:03.047477Z digest=sha256:72b330a2833911c609afa3b79641b0d50d6e16e1d5cd28f3cf1f7306a3017c40

Observation bb8bba7a-dd3f-4a25-91dd-b330a1a9bd86 · outbound

This paper cites R., Millar, J.

A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction R., Millar, J

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:28:05.506695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T23:28:03.187451Z digest=sha256:9f9815ac4349d164e320e4f6ae5202490583695640be4c1f39458025128554bf

Observation 05c36101-e931-437c-83b0-c48dceaf580e · outbound

This paper cites an unresolved cited work.

A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction Unresolved cited work

Reference 48

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:28:05.324738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T23:28:03.280247Z digest=sha256:e09bbac1bb65dceb371711fb8da4825c978652f9e2562a602e73e3306349570b

Observation badce5f1-8155-4fa8-90fc-6872b6849814 · outbound

This paper cites an unresolved cited work.

A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction Unresolved cited work

Reference 49

Resolution
malformed identifier
raw_fallback, observed 2026-08-06T23:28:05.047056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T23:28:03.401542Z digest=sha256:6cdba7b35f01b3e7d4b230409fd2a2dc7be9097f91bbe09f0cbc8841eece2ba1

Observation 543d5193-1bc8-4743-8751-843ab156c9c9 · outbound

This paper cites an unresolved cited work.

A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction Unresolved cited work

Reference 50

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:28:04.644757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T23:28:03.509557Z digest=sha256:7bcf63a4a033a9b5fe26dffc3c4af3efaba015d99f68cb330b70cd61f295985c

Observation 7e8da6d9-91fa-4435-a140-b17d7b343655 · outbound

This paper cites conc ” and “ ∆conc.

A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction conc ” and “ ∆conc

Reference 51

Resolution
malformed identifier
raw_fallback, observed 2026-08-06T23:28:04.384322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-06T23:28:03.616671Z digest=sha256:475d687e76ec313a84978bf44fdbd744f804c1d8e9732c1ae20387b090c7fad2

Pith citing papers

No inbound Pith citation observations are available.