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Paper Citation Record · LEDGER

Preventing the Generation of Inconsistent Sets of Classification Rules

As of 16 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:1908.09652.

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

pith.paper-citation-record.v1
1908.09652 v2

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T11:34:16.748415Z

measured 26 of 26 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

26 of 26 outbound references displayed

  • verified exact1
  • verified fuzzy19
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f783742f-15ca-457c-946f-774c92c6135c · outbound

This paper cites Improving the interpretability of classi- fication rules discovered by an ant colony algorithm,.

Preventing the Generation of Inconsistent Sets of Classification Rules Improving the interpretability of classi- fication rules discovered by an ant colony algorithm,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:34:17.142361Z

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 a841dd8d-7675-485e-b957-2092491c56a8 · outbound

This paper cites European Union regulations on algorithmic decision-making and a "right to explanation".

Preventing the Generation of Inconsistent Sets of Classification Rules European Union regulations on algorithmic decision-making and a "right to explanation"

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-14T11:34:16.645460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T11:34:16.645460Z digest=sha256:9ac39ab2073f985c24e22da7849bf3387f7107f62d41df593d878cbc568900e1

Observation 56978745-ce57-4e61-8a5c-d47055534107 · outbound

This paper cites The Mythos of Model Interpretability.

Preventing the Generation of Inconsistent Sets of Classification Rules The Mythos of Model Interpretability

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-14T11:34:16.650102Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T11:34:16.650102Z digest=sha256:f150882112ebae6f5763ebd0df3df8f86b03ddbcd0e7870e34b751b7432afe37

Observation 5f4dd1bd-f660-4065-983f-a26c514c7efe · outbound

This paper cites Induction of decision trees,.

Preventing the Generation of Inconsistent Sets of Classification Rules Induction of decision trees,

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-14T11:34:16.654358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 3cb4334a-bb02-4ff9-8204-76166669958b · outbound

This paper cites Deep learning,.

Preventing the Generation of Inconsistent Sets of Classification Rules Deep learning,

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-14T11:34:16.658424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T11:34:16.658424Z digest=sha256:ba4166eb4cc054e1d1fb4c4f81f70b863c78b7bd7463906a3acb545927119371

Observation 4b3ae3bc-4b21-4412-9bfa-2710c50a443c · outbound

This paper cites Comprehensible classification models: a position paper,.

Preventing the Generation of Inconsistent Sets of Classification Rules Comprehensible classification models: a position paper,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:34:17.106984Z

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.

source=pdf_text observed=2026-08-14T11:34:16.663004Z digest=sha256:eee4589532ab249c568dd75fed4c206628d1207d3bc62720deb448d11cae3bbd

Observation 9a064ed0-a0af-420c-9181-700b5af68f6c · outbound

This paper cites Case- based explanation of non-case-based learning methods.

Preventing the Generation of Inconsistent Sets of Classification Rules Case- based explanation of non-case-based learning methods

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:34:17.092547Z

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.

source=pdf_text observed=2026-08-14T11:34:16.667888Z digest=sha256:39bbacc7eee884aa1955329842ca520520b153ad81580179795daffa439e83fa

Observation e0096107-ce09-4a3a-bbe7-5e4303380fee · outbound

This paper cites What is a learning classifier system?.

Preventing the Generation of Inconsistent Sets of Classification Rules What is a learning classifier system?

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:34:17.077868Z

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 66738c22-ea30-4bc1-9654-33728f43753f · outbound

This paper cites Why Interpretability in Machine Learning? An Answer Using Distributed Detection and Data Fusion Theory.

Preventing the Generation of Inconsistent Sets of Classification Rules Why Interpretability in Machine Learning? An Answer Using Distributed Detection and Data Fusion Theory

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-14T11:34:16.793362Z

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 7c3a0d46-8d87-4dd6-a986-1e970dd2da12 · outbound

This paper cites Cognitive systems: Toward human-level functionality.

Preventing the Generation of Inconsistent Sets of Classification Rules Cognitive systems: Toward human-level functionality

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:34:17.064004Z

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 70099cf6-5b7b-4471-9442-fcfb3489b431 · outbound

This paper cites A hierarchical multi- label classification ant colony algorithm for protein function prediction,.

Preventing the Generation of Inconsistent Sets of Classification Rules A hierarchical multi- label classification ant colony algorithm for protein function prediction,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:34:17.050418Z

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 554328e0-aeb8-49c8-a584-42055af3122e · outbound

This paper cites an unresolved cited work.

Preventing the Generation of Inconsistent Sets of Classification Rules Unresolved cited work

Reference 12

Resolution
unresolved
raw_fallback, observed 2026-08-14T11:34:17.035909Z

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 9faa86ba-71bc-4040-b734-d8b09e80818a · outbound

This paper cites Knowledge discovery in multi-label pheno- type data,.

Preventing the Generation of Inconsistent Sets of Classification Rules Knowledge discovery in multi-label pheno- type data,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:34:17.021159Z

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.

source=pdf_text observed=2026-08-14T11:34:16.692934Z digest=sha256:f54e4ea7d31f355602ad460b1780b746bfc321a3566d9a92ce75c48fef151e93

Observation d5e95d74-22c8-4aaf-8942-871d08082e6c · outbound

This paper cites Hierarchical multi-classification,.

Preventing the Generation of Inconsistent Sets of Classification Rules Hierarchical multi-classification,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:34:17.006701Z

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 b42890e4-2769-439c-8433-32cb525c3aff · outbound

This paper cites Top-down induction of clus- tering trees,.

Preventing the Generation of Inconsistent Sets of Classification Rules Top-down induction of clus- tering trees,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:34:16.993494Z

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 87827c6c-ba64-441f-a38f-07a5c6e320d3 · outbound

This paper cites Deci- sion trees for hierarchical multi-label classification,.

Preventing the Generation of Inconsistent Sets of Classification Rules Deci- sion trees for hierarchical multi-label classification,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:34:16.979439Z

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 f6d601d9-d787-41df-89f7-7285167485cb · outbound

This paper cites Predicting gene function using hierarchical multi-label decision tree ensembles,.

Preventing the Generation of Inconsistent Sets of Classification Rules Predicting gene function using hierarchical multi-label decision tree ensembles,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:34:16.963405Z

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 569a3405-3144-41f6-bb7d-0370b0adfba7 · outbound

This paper cites Agent-based evolutionary approach for interpretable rule-based knowledge extrac- tion,.

Preventing the Generation of Inconsistent Sets of Classification Rules Agent-based evolutionary approach for interpretable rule-based knowledge extrac- tion,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:34:16.948896Z

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 1bc9bafa-6f87-4b36-8902-198b813907ee · outbound

This paper cites A fast and elitist multiobjective genetic algorithm: Nsga-ii,.

Preventing the Generation of Inconsistent Sets of Classification Rules A fast and elitist multiobjective genetic algorithm: Nsga-ii,

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-14T11:34:16.716610Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c43dd3d7-fba8-404b-8273-e405d81b09a8 · outbound

This paper cites A genetic algorithm for hierarchical multi-label classification,.

Preventing the Generation of Inconsistent Sets of Classification Rules A genetic algorithm for hierarchical multi-label classification,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:34:16.924452Z

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 159f5858-f2ce-4311-aa49-0062415d8a55 · outbound

This paper cites A survey of genetic algorithms for multi-label classification,.

Preventing the Generation of Inconsistent Sets of Classification Rules A survey of genetic algorithms for multi-label classification,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:34:16.911107Z

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 107a2cff-a6ef-4547-9627-7dcbc76544ea · outbound

This paper cites Data mining with an ant colony optimization algorithm,.

Preventing the Generation of Inconsistent Sets of Classification Rules Data mining with an ant colony optimization algorithm,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:34:16.896518Z

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 25c894ac-8f8f-47f7-85b3-366eb71d3c0f · outbound

This paper cites A new ant colony algorithm for multi-label classification with applications in bioinfomatics,.

Preventing the Generation of Inconsistent Sets of Classification Rules A new ant colony algorithm for multi-label classification with applications in bioinfomatics,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:34:16.882169Z

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.

source=pdf_text observed=2026-08-14T11:34:16.734519Z digest=sha256:dd7927ada473835b18275741f5e1acfe7f95cc99573a762ff9acafec12c97ac0

Observation 1cb8b9ab-4c4a-4974-9606-d63b983c23d0 · outbound

This paper cites cant-miner: an ant colony classification algorithm to cope with continuous attributes,.

Preventing the Generation of Inconsistent Sets of Classification Rules cant-miner: an ant colony classification algorithm to cope with continuous attributes,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:34:16.867634Z

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.

source=pdf_text observed=2026-08-14T11:34:16.739293Z digest=sha256:a8a0a964e9a7f720d6a75dd38af7ba85883df335e3d2ca1a2b3d9e6b79f78be6

Observation a7aa4162-927e-4a62-abd1-0c434cc005cb · outbound

This paper cites A hierarchical classification ant colony algorithm for predicting gene ontology terms,.

Preventing the Generation of Inconsistent Sets of Classification Rules A hierarchical classification ant colony algorithm for predicting gene ontology terms,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:34:16.852614Z

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.

source=pdf_text observed=2026-08-14T11:34:16.743594Z digest=sha256:4e90165a9448722fd36a813ebcccbe50842f458e80004cacd8e4a69d782d28d8

Observation 3b5873ab-2130-4007-b7c5-eb678bc4176b · outbound

This paper cites A new sequential covering strategy for inducing classification rules with ant colony algorithms.

Preventing the Generation of Inconsistent Sets of Classification Rules A new sequential covering strategy for inducing classification rules with ant colony algorithms

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:34:16.837782Z

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.

source=pdf_text observed=2026-08-14T11:34:16.748415Z digest=sha256:761f972cc81d0616b831c6dfda254a149a916ac4986225ff6e7aa2bbd34e8e65

Pith citing papers

No inbound Pith citation observations are available.