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Paper Citation Record · LEDGER

Enhancing interpretability of rule-based classifiers through feature graphs

As of 17 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2506.13903.

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

pith.paper-citation-record.v1
2506.13903 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:31:24.039004Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

28 of 28 outbound references displayed

  • verified exact0
  • verified fuzzy25
  • unresolved3
  • parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a90f9a9c-7ecf-4add-a740-05b598d0acc5 · outbound

This paper cites Bioinformatics26(10), 1340–1347 (2010).

Enhancing interpretability of rule-based classifiers through feature graphs Bioinformatics26(10), 1340–1347 (2010)

Reference 1

Resolution
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Source-reported events for the cited work

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Observation 8cd9c90a-d15b-4c9d-a6bd-9d2d39a6367b · outbound

This paper cites IEEE journal of biomedical and health in- formatics19(5), 1557–1566 (2015).

Enhancing interpretability of rule-based classifiers through feature graphs IEEE journal of biomedical and health in- formatics19(5), 1557–1566 (2015)

Reference 2

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 51b9a523-d89e-4ea4-a793-9ad76e55b9d8 · outbound

This paper cites Expert Systems with Applications39(14), 11766–11774 (2012).

Enhancing interpretability of rule-based classifiers through feature graphs Expert Systems with Applications39(14), 11766–11774 (2012)

Reference 3

Resolution
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Observation aec052a9-9093-4693-a261-6657099cd384 · outbound

This paper cites In: Machine learning proceedings 1995, pp.

Enhancing interpretability of rule-based classifiers through feature graphs In: Machine learning proceedings 1995, pp

Reference 4

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Source-reported events for the cited work

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Observation 4fb81ffa-9bed-4296-9244-41f5a2eb101e · outbound

This paper cites Computers in Biology and Medicine162, 107064 (2023).

Enhancing interpretability of rule-based classifiers through feature graphs Computers in Biology and Medicine162, 107064 (2023)

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 3c8e258c-9fdb-4bd8-bbb8-6ebeada70323 · outbound

This paper cites Computers12(6), 123 (2023).

Enhancing interpretability of rule-based classifiers through feature graphs Computers12(6), 123 (2023)

Reference 6

Resolution
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Source-reported events for the cited work

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Observation 1e363937-d4b1-4d84-87ad-7254d05e9b35 · outbound

This paper cites Bmj327(7425), 1219–1221 (2003).

Enhancing interpretability of rule-based classifiers through feature graphs Bmj327(7425), 1219–1221 (2003)

Reference 7

Resolution
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Source-reported events for the cited work

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Observation 41fc9d20-1b82-4c0d-8c30-a3b43a84dacd · outbound

This paper cites an unresolved cited work.

Enhancing interpretability of rule-based classifiers through feature graphs Unresolved cited work

Reference 8

Resolution
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Source-reported events for the cited work

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Observation 78a60862-df4c-4cea-8765-de84dbe90615 · outbound

This paper cites Journal of pain and symptom management53(3), 571–577 (2017) 16 C.

Enhancing interpretability of rule-based classifiers through feature graphs Journal of pain and symptom management53(3), 571–577 (2017) 16 C

Reference 9

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation b9d27541-cca2-42a5-a320-8d03cfdf7dfb · outbound

This paper cites Data & Knowledge Engineering63(1), 167–182 (2007).

Enhancing interpretability of rule-based classifiers through feature graphs Data & Knowledge Engineering63(1), 167–182 (2007)

Reference 10

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Source-reported events for the cited work

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Observation 3d75f92f-3e05-488a-b7de-992191bab063 · outbound

This paper cites KR91, 387–394 (1991).

Enhancing interpretability of rule-based classifiers through feature graphs KR91, 387–394 (1991)

Reference 11

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation f98b06e2-24ca-4420-aa29-0d7f80192918 · outbound

This paper cites In: Machine Learning and Knowledge DiscoveryinDatabases,2010,Proceedings,PartII21.pp.145–161.Springer(2010).

Enhancing interpretability of rule-based classifiers through feature graphs In: Machine Learning and Knowledge DiscoveryinDatabases,2010,Proceedings,PartII21.pp.145–161.Springer(2010)

Reference 12

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation b9a58e62-2741-479b-b098-7a338d270dd9 · outbound

This paper cites IEEE Journal of Biomedical and Health Informatics (2023).

Enhancing interpretability of rule-based classifiers through feature graphs IEEE Journal of Biomedical and Health Informatics (2023)

Reference 13

Resolution
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Observation 250f7a8a-9a1e-4487-b16f-d3de99cfb0aa · outbound

This paper cites In: 2016 IEEE 8th International Conference on Intelligent Systems (IS).

Enhancing interpretability of rule-based classifiers through feature graphs In: 2016 IEEE 8th International Conference on Intelligent Systems (IS)

Reference 14

Resolution
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Source-reported events for the cited work

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Observation 9ede28f9-72ba-4dce-9555-467551c1ffd4 · outbound

This paper cites In: 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

Enhancing interpretability of rule-based classifiers through feature graphs In: 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 80dfe421-8bee-422f-a222-a8396599baee · outbound

This paper cites Advances in neural information processing systems30(2017).

Enhancing interpretability of rule-based classifiers through feature graphs Advances in neural information processing systems30(2017)

Reference 16

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 9f325598-0aa3-4d14-8ebe-5f19bab42b49 · outbound

This paper cites Diabetologia 63, 519–527 (2020).

Enhancing interpretability of rule-based classifiers through feature graphs Diabetologia 63, 519–527 (2020)

Reference 17

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 836c9000-133a-4515-aba4-c059d863e876 · outbound

This paper cites International Journal of Academic Information Systems Research (IJAISR)3(7), 1–23 (2019).

Enhancing interpretability of rule-based classifiers through feature graphs International Journal of Academic Information Systems Research (IJAISR)3(7), 1–23 (2019)

Reference 18

Resolution
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This paper cites In: Biomedical informatics: computer applications in health care and biomedicine, pp.

Enhancing interpretability of rule-based classifiers through feature graphs In: Biomedical informatics: computer applications in health care and biomedicine, pp

Reference 19

Resolution
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Observation db6976e8-98ab-4e27-8a33-8d49f3e1c0d3 · outbound

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Enhancing interpretability of rule-based classifiers through feature graphs Unresolved cited work

Reference 20

Resolution
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This paper cites IEEE Transactions on Fuzzy Systems21(6), 1133–1149 (2013).

Enhancing interpretability of rule-based classifiers through feature graphs IEEE Transactions on Fuzzy Systems21(6), 1133–1149 (2013)

Reference 21

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 329da5bb-c82d-40ad-bc99-1d07217743ec · outbound

This paper cites Information9(1), 6 (2018).

Enhancing interpretability of rule-based classifiers through feature graphs Information9(1), 6 (2018)

Reference 22

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 8190c9c3-6838-4f37-848d-97923cb79e51 · outbound

This paper cites Data mining and knowledge discovery handbook pp.

Enhancing interpretability of rule-based classifiers through feature graphs Data mining and knowledge discovery handbook pp

Reference 23

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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This paper cites In: CEUR WORKSHOP PROCEED- INGS.

Enhancing interpretability of rule-based classifiers through feature graphs In: CEUR WORKSHOP PROCEED- INGS

Reference 24

Resolution
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Source-reported events for the cited work

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Observation 6efb77a2-73ce-4226-a35f-22e8a4f883e5 · outbound

This paper cites BMC Medical Informatics and Decision Making24 (Suppl 4), 186 (2024).

Enhancing interpretability of rule-based classifiers through feature graphs BMC Medical Informatics and Decision Making24 (Suppl 4), 186 (2024)

Reference 25

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 66e0e311-8107-4ca0-bddc-15adb89241a8 · outbound

This paper cites Artificial Intelligence Review53(2), 907– 948 (2020).

Enhancing interpretability of rule-based classifiers through feature graphs Artificial Intelligence Review53(2), 907– 948 (2020)

Reference 26

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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This paper cites In: Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining.

Enhancing interpretability of rule-based classifiers through feature graphs In: Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 955c3bd6-4f00-49df-84c1-805f759c3f83 · outbound

This paper cites Physical review E76(4), 046115 (2007).

Enhancing interpretability of rule-based classifiers through feature graphs Physical review E76(4), 046115 (2007)

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Pith citing papers

No inbound Pith citation observations are available.