Paper Citation Record · LEDGER

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling?

As of 9 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2606.01305.

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

pith.paper-citation-record.v1
2606.01305 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-28T16:53:17.681575Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

32 of 32 outbound references displayed

verified exact1
verified fuzzy0
unresolved29
parse uncertain0
malformed identifier0
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 68d65126-b629-463a-ac46-ae62d1ebbf79 · outbound

This paper cites Calphad82, 102580 (2023).

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? Calphad82, 102580 (2023)

Reference 1

Resolution: unresolved; no resolver link, observed 2026-06-28T16:53:17.681575Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9af52574-f7e3-4e72-be1f-6ca059623acb · outbound

This paper cites Jom49, 14–19 (1997).

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? Jom49, 14–19 (1997)

Reference 2

Resolution: unresolved; no resolver link, observed 2026-06-28T16:53:17.681575Z

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Observation 67a75e99-e6f9-487f-82d6-125a82445d76 · outbound

This paper cites Calphad26(2), 273–312 (2002).

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? Calphad26(2), 273–312 (2002)

Reference 3

Resolution: unresolved; no resolver link, observed 2026-06-28T16:53:17.681575Z

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Observation b1a0e19d-9e54-4bc7-9734-7c33c0b9d680 · outbound

This paper cites Calphad 26(2), 175–188 (2002).

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? Calphad 26(2), 175–188 (2002)

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-28T16:53:17.681575Z

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Observation 8282d5f5-c618-41fa-aabd-a1c6324ef2ab · outbound

This paper cites Integrating Materials and Manufacturing Innovation4(1), 1–15 (2015).

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? Integrating Materials and Manufacturing Innovation4(1), 1–15 (2015)

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-28T16:53:17.681575Z

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Observation 705cde7d-479f-4e44-9c5f-4ffafe3fa875 · outbound

This paper cites Materials Science and Engineering: R: Reports146, 100644 (2021).

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? Materials Science and Engineering: R: Reports146, 100644 (2021)

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-28T16:53:17.681575Z

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Observation 7c5c1c1a-c63c-40c6-b9e6-42d72cfdb503 · outbound

This paper cites Materials & design202, 109532 (2021).

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? Materials & design202, 109532 (2021)

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-28T16:53:17.681575Z

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Observation 07750eeb-11ed-410a-9aa9-4fbd80006c58 · outbound

This paper cites Scripta Materialia249, 116180 (2024).

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? Scripta Materialia249, 116180 (2024)

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-28T16:53:17.681575Z

Source-reported events for the cited work

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Observation 9d26bcbc-98de-4260-bf26-5fd5e148e4d4 · outbound

This paper cites Journal of Alloys and Compounds960, 170543 (2023).

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? Journal of Alloys and Compounds960, 170543 (2023)

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-28T16:53:17.681575Z

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Observation 267136b3-3cb9-4de9-bf2c-647d99142761 · outbound

This paper cites Acta Materialia198, 178–222 (2020) 21.

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? Acta Materialia198, 178–222 (2020) 21

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-28T16:53:17.681575Z

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Observation dd7697ea-3d7e-4d3d-96b2-66d1d52d5ba1 · outbound

This paper cites Journal of Materials Research and Technology26, 1341–1374 (2023).

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? Journal of Materials Research and Technology26, 1341–1374 (2023)

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-28T16:53:17.681575Z

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Observation 76dae038-a353-49c4-bc28-f0ebda0f5278 · outbound

This paper cites Journal of Materials Research and Technology30, 5381–5393 (2024).

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? Journal of Materials Research and Technology30, 5381–5393 (2024)

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-28T16:53:17.681575Z

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Observation e3f0b72a-2105-44c7-a4e5-d49c825e1778 · outbound

This paper cites Materials Today Communications30, 103172 (2022).

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? Materials Today Communications30, 103172 (2022)

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-28T16:53:17.681575Z

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Observation 07072f06-53ce-4eab-bc02-0f22ec69cae6 · outbound

This paper cites npj Computational Materials6(1), 50 (2020).

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? npj Computational Materials6(1), 50 (2020)

Reference 14

Resolution: unresolved; no resolver link, observed 2026-06-28T16:53:17.681575Z

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Observation a8af110b-84fe-4c7a-91e7-bcf7f876a389 · outbound

This paper cites npj Computational Materials9(1), 68 (2023).

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? npj Computational Materials9(1), 68 (2023)

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-28T16:53:17.681575Z

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Observation ee636a7d-9751-4a06-86a4-c0ba659ab1d3 · outbound

This paper cites npj Computational Materials10(1), 172 (2024).

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? npj Computational Materials10(1), 172 (2024)

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-28T16:53:17.681575Z

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Observation ca2e2407-7171-43f8-89c6-9b36f0ab571c · outbound

This paper cites npj Computational Materials10(1), 274 (2024).

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? npj Computational Materials10(1), 274 (2024)

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-28T16:53:17.681575Z

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Observation 4d149b8b-bad4-4d9a-a7a7-7761edc00ddf · outbound

This paper cites Scientific Reports9(1), 15501 (2019).

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? Scientific Reports9(1), 15501 (2019)

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-28T16:53:17.681575Z

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Observation 4c041beb-a4c4-48e1-9b86-9fc11c14d06b · outbound

This paper cites MRS Bulletin47(2), 158–167 (2022).

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? MRS Bulletin47(2), 158–167 (2022)

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-28T16:53:17.681575Z

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Observation 7ecb08bc-e7e9-4e15-9d9b-4780faba1305 · outbound

This paper cites Calphad15(4), 317–425 (1991).

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? Calphad15(4), 317–425 (1991)

Reference 20

Resolution: unresolved; no resolver link, observed 2026-06-28T16:53:17.681575Z

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Observation 465cefc6-ea7f-4ed0-8f43-1974549c34e1 · outbound

This paper cites Computational Materials Science258, 113970 (2025).

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? Computational Materials Science258, 113970 (2025)

Reference 21

Resolution: unresolved; no resolver link, observed 2026-06-28T16:53:17.681575Z

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Observation bbb22e26-a04d-4475-8883-92dcd4fdd8f1 · outbound

This paper cites Deep learning for CALPHAD modeling: Universal parameter learning solely based on chemical formula.

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? Deep learning for CALPHAD modeling: Universal parameter learning solely based on chemical formula

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-07-01T21:26:16.538445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c344ce2f-2007-4ba1-afda-78e419d6c10a · outbound

This paper cites AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data.

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data

Reference 23

Resolution: metadata mismatch; local_arxiv, observed 2026-07-01T21:26:16.541309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7f0696d2-ce33-4cd4-98f5-94f87b2d1b14 · outbound

This paper cites npj Computational Materials2(1), 1–7 (2016).

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? npj Computational Materials2(1), 1–7 (2016)

Reference 24

Resolution: unresolved; no resolver link, observed 2026-06-28T16:53:17.681575Z

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Observation 910575b7-1949-484b-9fbd-f913b01c56b1 · outbound

This paper cites Computational Materials Science152, 60–69 (2018).

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? Computational Materials Science152, 60–69 (2018)

Reference 25

Resolution: unresolved; no resolver link, observed 2026-06-28T16:53:17.681575Z

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Observation 14b13879-d3e6-41c8-9a08-0947b49c7b58 · outbound

This paper cites Journal of Physics: Condensed Matter29(27), 273002 (2017).

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? Journal of Physics: Condensed Matter29(27), 273002 (2017)

Reference 26

Resolution: unresolved; no resolver link, observed 2026-06-28T16:53:17.681575Z

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Observation 7b73b9ce-0a12-4d59-89c5-760e82edda8f · outbound

This paper cites an unresolved cited work.

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? Unresolved cited work

Reference 27

Resolution: unresolved; no resolver link, observed 2026-06-28T16:53:17.681575Z

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Observation cddad8a9-938d-49dc-bc8d-5b383e43a84c · outbound

This paper cites MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures.

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures

Reference 28

Resolution: metadata mismatch; local_arxiv, observed 2026-07-01T21:26:16.544055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 34e30cdf-6ce3-4c2c-9ebb-9fd5ad539f8e · outbound

This paper cites Journal of British Surgery105(10), 1348–1348 (2018).

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? Journal of British Surgery105(10), 1348–1348 (2018)

Reference 29

Resolution: unresolved; no resolver link, observed 2026-06-28T16:53:17.681575Z

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Observation ec883373-81ad-40b6-8885-117fe849bd85 · outbound

This paper cites the Journal of machine Learning research12, 2825–2830 (2011).

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? the Journal of machine Learning research12, 2825–2830 (2011)

Reference 30

Resolution: unresolved; no resolver link, observed 2026-06-28T16:53:17.681575Z

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Observation aa371750-e48e-4fbc-bb97-da12f113389d · outbound

This paper cites Thermochimica acta129(1), 71–75 (1988).

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? Thermochimica acta129(1), 71–75 (1988)

Reference 31

Resolution: unresolved; no resolver link, observed 2026-06-28T16:53:17.681575Z

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Observation 950a308a-2409-40e3-b555-ce6c63b7a9da · outbound

This paper cites Computational Materials Science68, 314–319 (2013) 23.

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? Computational Materials Science68, 314–319 (2013) 23

Reference 32

Resolution: unresolved; no resolver link, observed 2026-06-28T16:53:17.681575Z

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Pith citing papers

No inbound Pith citation observations are available.