Paper Citation Record · LEDGER

Enhancing Experimental Efficiency in Materials Design: A Comparative Study of Taguchi and Machine Learning Methods

As of 12 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:2506.03910.

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

pith.paper-citation-record.v1
2506.03910 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:57:37.730572Z

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

12 of 12 outbound references displayed

verified exact4
verified fuzzy2
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 30e21b62-1c56-4490-82d7-feb027f124ee · outbound

This paper cites an unresolved cited work.

Enhancing Experimental Efficiency in Materials Design: A Comparative Study of Taguchi and Machine Learning Methods Unresolved cited work

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T10:57:37.701123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 553ea705-cd95-4561-b4b2-2ddff7c2d25e · outbound

This paper cites an unresolved cited work.

Enhancing Experimental Efficiency in Materials Design: A Comparative Study of Taguchi and Machine Learning Methods Unresolved cited work

Reference 2

Resolution: verified exact; doi, observed 2026-08-07T10:57:37.797733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e5112d3c-3428-4a4e-8bbe-3a11ed04f27e · outbound

This paper cites an unresolved cited work.

Enhancing Experimental Efficiency in Materials Design: A Comparative Study of Taguchi and Machine Learning Methods Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:57:37.902569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 138634ce-e978-4d3b-9f66-0d15190d43d7 · outbound

This paper cites Dinovitzer, X.

Enhancing Experimental Efficiency in Materials Design: A Comparative Study of Taguchi and Machine Learning Methods Dinovitzer, X

Reference 4

Resolution: verified exact; doi, observed 2026-08-07T10:57:37.789241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 2ecbdfc3-d5dd-4486-bb13-827df2063b2d · outbound

This paper cites Lin, J.-C.

Enhancing Experimental Efficiency in Materials Design: A Comparative Study of Taguchi and Machine Learning Methods Lin, J.-C

Reference 5

Resolution: verified exact; doi, observed 2026-08-07T10:57:37.781117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d9c49078-0b33-48df-a0ae-b2aa0fa888bd · outbound

This paper cites Batra, L.

Enhancing Experimental Efficiency in Materials Design: A Comparative Study of Taguchi and Machine Learning Methods Batra, L

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T10:57:37.715110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a2fe4df-cfc0-483f-8d67-ff1a8cad1d47 · outbound

This paper cites an unresolved cited work.

Enhancing Experimental Efficiency in Materials Design: A Comparative Study of Taguchi and Machine Learning Methods Unresolved cited work

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T10:57:37.717908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff2050de-835f-4563-90f9-4e2157ace92d · outbound

This paper cites an unresolved cited work.

Enhancing Experimental Efficiency in Materials Design: A Comparative Study of Taguchi and Machine Learning Methods Unresolved cited work

Reference 8

Resolution: verified exact; doi, observed 2026-08-07T10:57:37.763083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e6279ef2-42dc-4d0e-85c7-0dbaa84db58a · outbound

This paper cites an unresolved cited work.

Enhancing Experimental Efficiency in Materials Design: A Comparative Study of Taguchi and Machine Learning Methods Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:57:37.895293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f0bccdcc-f966-4576-b5a5-6cfb422b3ea7 · outbound

This paper cites Settles, Active learning literature survey, Technical Report 1648, University of Wisconsin-Madison, Dept.

Enhancing Experimental Efficiency in Materials Design: A Comparative Study of Taguchi and Machine Learning Methods Settles, Active learning literature survey, Technical Report 1648, University of Wisconsin-Madison, Dept

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:57:37.887744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation cc79769b-984f-4c17-a8b7-62a40cd4ce2c · outbound

This paper cites Geron, Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems, 2nd Edition, O’Reilly Media, Inc., 2019.

Enhancing Experimental Efficiency in Materials Design: A Comparative Study of Taguchi and Machine Learning Methods Geron, Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems, 2nd Edition, O’Reilly Media, Inc., 2019

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:57:37.879981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5b35a68a-4de2-46b1-a48b-041fb452b7c3 · outbound

This paper cites Mattera, G.

Enhancing Experimental Efficiency in Materials Design: A Comparative Study of Taguchi and Machine Learning Methods Mattera, G

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T10:57:37.730572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.