Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-01T01:25:40.982423Z
Paper Citation Record · LEDGER
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility
As of 15 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 0 inbound Pith citation observations for arXiv:2607.25827.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
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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- verified fuzzy0
- unresolved53
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 54572254-2f8b-4f08-9c5f-8dfdac0e868e · outbound
This paper cites Physics reports , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Physics reports , volume=
Reference 1
- Resolution
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- no resolver link, observed 2026-08-01T01:25:40.872327Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 44b96720-2afd-4473-bf12-ffff3767c8ef · outbound
This paper cites Reports on Progress in Physics , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Reports on Progress in Physics , volume=
Reference 2
- Resolution
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Unavailable: canonical work link unavailable.
Observation 4e18c4bf-f74d-4bfd-ad24-c98191274c3c · outbound
This paper cites Biophysical journal , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Biophysical journal , volume=
Reference 3
- Resolution
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- no resolver link, observed 2026-08-01T01:25:40.878623Z
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Unavailable: canonical work link unavailable.
Observation c6a4d962-427a-475d-b352-567edb7ec6c6 · outbound
This paper cites Biophysical journal , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Biophysical journal , volume=
Reference 4
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4670499f-411f-4c74-b25c-37a29ecaba39 · outbound
This paper cites Biophysical journal , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Biophysical journal , volume=
Reference 5
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Source-reported events for the cited work
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Observation c9cd5c28-1577-4963-a80d-773ada1c71ca · outbound
This paper cites ACS biomaterials science & engineering , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility ACS biomaterials science & engineering , volume=
Reference 6
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f62bc8a2-530c-4a35-ab22-d1ef54f7a26e · outbound
This paper cites Proceedings of the National Academy of Sciences , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Proceedings of the National Academy of Sciences , volume=
Reference 7
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 25d46eeb-9d2c-4cb0-bed8-7f81e735b65c · outbound
This paper cites The journal of physical chemistry letters , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility The journal of physical chemistry letters , volume=
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T01:25:40.889774Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0dcda188-2ee9-487d-a5b1-9aecfa775847 · outbound
This paper cites New Journal of Physics , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility New Journal of Physics , volume=
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T01:25:40.891779Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f1c3e515-5e7c-4d99-838d-5594542d5d9d · outbound
This paper cites Journal of Physics: Condensed Matter , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Journal of Physics: Condensed Matter , volume=
Reference 10
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ce98bd16-fd46-4bd2-9bef-3427309d808d · outbound
This paper cites Nature , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Nature , volume=
Reference 11
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Unavailable: canonical work link unavailable.
Observation b925e6f8-3f8f-497f-a67c-6957c7c25d7e · outbound
This paper cites Nature communications , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Nature communications , volume=
Reference 12
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- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6e50ec64-dea6-4a87-bc22-10c8a56a5637 · outbound
This paper cites The European Physical Journal Plus , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility The European Physical Journal Plus , volume=
Reference 13
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c89c4d80-c7e3-4661-86e8-a8a9f67dd5e8 · outbound
This paper cites Biophysical journal , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Biophysical journal , volume=
Reference 14
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d14afbab-e570-493c-bb4e-d42f4e16c126 · outbound
This paper cites Nature computational science , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Nature computational science , volume=
Reference 15
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 30f6783b-9dd8-470b-a9c9-dea0580a26ac · outbound
This paper cites The Journal of Chemical Physics , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility The Journal of Chemical Physics , volume=
Reference 16
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Unavailable: canonical work link unavailable.
Observation ce3052c2-88a7-4b29-987a-9472a69b9da6 · outbound
This paper cites Physical Review E , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Physical Review E , volume=
Reference 17
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5cff1e19-20fd-4345-9f8a-d6f1c5e67ba4 · outbound
This paper cites Reviews of modern physics , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Reviews of modern physics , volume=
Reference 18
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Unavailable: canonical work link unavailable.
Observation 08bcbea5-1de3-43fd-a6f1-8de28ae3d5cf · outbound
This paper cites Physical review letters , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Physical review letters , volume=
Reference 19
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Unavailable: canonical work link unavailable.
Observation a94f2923-60dd-4340-b961-bca8da14eee0 · outbound
This paper cites ACS nano , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility ACS nano , volume=
Reference 20
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Unavailable: canonical work link unavailable.
Observation ff64684f-5740-4f3c-a594-37c99d8544d6 · outbound
This paper cites The Journal of Chemical Physics , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility The Journal of Chemical Physics , volume=
Reference 21
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Unavailable: canonical work link unavailable.
Observation fcbeb59b-ed47-4622-a942-ec0470fd4003 · outbound
This paper cites National Science Review , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility National Science Review , volume=
Reference 22
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Unavailable: canonical work link unavailable.
Observation ac956c25-0f22-4e87-83bd-cb24f9c64431 · outbound
This paper cites The Journal of Physical Chemistry B , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility The Journal of Physical Chemistry B , volume=
Reference 23
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Unavailable: canonical work link unavailable.
Observation 969188f9-35da-41cf-b86f-e91113430687 · outbound
This paper cites Europhysics Letters , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Europhysics Letters , volume=
Reference 24
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Unavailable: canonical work link unavailable.
Observation f1151a52-2843-459b-8892-7431bf4a8b9a · outbound
This paper cites The Journal of Physical Chemistry B , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility The Journal of Physical Chemistry B , volume=
Reference 25
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ce26809a-eb6c-46b0-a999-e5d6b4a64c04 · outbound
This paper cites Physical Review E , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Physical Review E , volume=
Reference 26
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6ccd18fc-c35c-4043-bf53-24a10ad4e63b · outbound
This paper cites The Journal of Chemical Physics , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility The Journal of Chemical Physics , volume=
Reference 27
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- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c02253b4-e1e8-4e14-b62d-3d8e4ec0431b · outbound
This paper cites Science advances , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Science advances , volume=
Reference 28
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5949f28f-7b01-4d6c-aaa1-cabad6ba277a · outbound
This paper cites The Journal of Chemical Physics , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility The Journal of Chemical Physics , volume=
Reference 29
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 410f368e-4302-4b26-98af-6b31894c42bf · outbound
This paper cites Advances in neural information processing systems , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Advances in neural information processing systems , volume=
Reference 30
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 41cb3306-e648-46db-9858-c2156772d70d · outbound
This paper cites Consistent Individualized Feature Attribution for Tree Ensembles.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Consistent Individualized Feature Attribution for Tree Ensembles
Reference 31
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bdd9c91b-25da-4f68-b80f-d69d845bebcf · outbound
This paper cites Chemical Science , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Chemical Science , volume=
Reference 32
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e633fc69-ae3a-41cb-bee4-fb2ba4c2695e · outbound
This paper cites Soft Matter , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Soft Matter , volume=
Reference 33
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a5e179bc-403c-4ec5-942e-4a41c4b992d6 · outbound
This paper cites Journal of Fluid Mechanics , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Journal of Fluid Mechanics , volume=
Reference 34
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 45c823ff-37ff-4f1d-98ee-b5ea37883d13 · outbound
This paper cites Machine learning , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Machine learning , volume=
Reference 35
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Unavailable: canonical work link unavailable.
Observation 1c79f0f4-369e-490c-ab45-86a529e6fc33 · outbound
This paper cites an unresolved cited work.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Unresolved cited work
Reference 36
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Unavailable: canonical work link unavailable.
Observation 8a90f001-421a-48e4-9daf-ed4a04104cbc · outbound
This paper cites Physical Review E , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Physical Review E , volume=
Reference 37
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9cb6fc00-7bf0-4115-9b2d-2c9c36cca1ad · outbound
This paper cites Physical Review Letters , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Physical Review Letters , volume=
Reference 38
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 24c1d557-3026-4294-9137-9e789bf7d835 · outbound
This paper cites Physical Review Letters , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Physical Review Letters , volume=
Reference 39
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3bb55229-8254-42ac-b846-c9d8b6607401 · outbound
This paper cites The Journal of chemical physics , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility The Journal of chemical physics , volume=
Reference 40
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation be8305ae-4921-409c-b92e-3c7d754f58fb · outbound
This paper cites Proceedings of the National Academy of Sciences , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Proceedings of the National Academy of Sciences , volume=
Reference 41
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f022a6a1-a732-49c4-a61b-ce445e5041fd · outbound
This paper cites Proceedings of the National Academy of Sciences , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Proceedings of the National Academy of Sciences , volume=
Reference 42
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2efa6a0d-e6ac-4b60-993a-fb5180ceac85 · outbound
This paper cites Reports on progress in Physics , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Reports on progress in Physics , volume=
Reference 43
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b648196b-e7f4-4536-9ef2-936e0752d5e5 · outbound
This paper cites Soft Matter , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Soft Matter , volume=
Reference 44
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation eaed522b-0fd1-46db-8383-4a6a780f9e5c · outbound
This paper cites Soft Matter , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Soft Matter , volume=
Reference 45
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 023a951c-ba76-4009-8898-1682db29646b · outbound
This paper cites The Journal of Chemical Physics , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility The Journal of Chemical Physics , volume=
Reference 46
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- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 15124363-4620-44c2-a33c-5644716fa395 · outbound
This paper cites Macromolecular Theory and Simulations , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Macromolecular Theory and Simulations , volume=
Reference 47
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- no resolver link, observed 2026-08-01T01:25:40.970011Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c487276f-d10b-4a11-9cb3-d958e11b6350 · outbound
This paper cites Computational Materials Science , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Computational Materials Science , volume=
Reference 48
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3c2ef585-4090-4192-88d9-ad8e31ad634b · outbound
This paper cites The Journal of Chemical Physics , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility The Journal of Chemical Physics , volume=
Reference 49
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a9b3832a-9f71-4a18-8760-2fb5ddd1c0d1 · outbound
This paper cites Soft matter , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Soft matter , volume=
Reference 50
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3b5b1012-ac26-4706-9061-f28018ceb391 · outbound
This paper cites ACS omega , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility ACS omega , volume=
Reference 51
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3050aa1e-b1e2-4d03-b078-baabea236bfc · outbound
This paper cites The Journal of Chemical Physics , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility The Journal of Chemical Physics , volume=
Reference 52
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d213ca6a-1378-410e-80d7-9a323cfa9480 · outbound
This paper cites Science , volume=.
Physics-Guided Interpretable Machine Learning Framework for Anomalous Transport in Crowded Media with Tunable Flexibility Science , volume=
Reference 53
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Unavailable: canonical work link unavailable.
Pith citing papers
No inbound Pith citation observations are available.