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Paper Citation Record · LEDGER

BACON: A fully explainable AI model with graded logic for decision making problems

As of 9 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2505.14510.

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

pith.paper-citation-record.v1
2505.14510 v3

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:36:09.403920Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

29 of 29 outbound references displayed

  • verified exact6
  • verified fuzzy11
  • unresolved12
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4e094d4e-8338-40ee-819a-0e434971923c · outbound

This paper cites Towards A Rigorous Science of Interpretable Machine Learning.

BACON: A fully explainable AI model with graded logic for decision making problems Towards A Rigorous Science of Interpretable Machine Learning

Reference 1

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unresolved
no resolver link, observed 2026-08-07T15:36:09.258006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 61fbf354-5c43-47b9-b0f2-0b5a48008af9 · outbound

This paper cites The Mythos of Model Interpretability.

BACON: A fully explainable AI model with graded logic for decision making problems The Mythos of Model Interpretability

Reference 2

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unresolved
no resolver link, observed 2026-08-07T15:36:09.263318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:36:09.263318Z digest=sha256:d1c4f3d373cfbd8b552c97c6e2e607e078ca60c12b5d1fad67eb00093011d8ed

Observation aef0fe34-db71-4395-acc5-82ee49a383a8 · outbound

This paper cites Interpretable Machine Learning.

BACON: A fully explainable AI model with graded logic for decision making problems Interpretable Machine Learning

Reference 3

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no resolver link, observed 2026-08-07T15:36:09.269024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 5a85bdbf-5098-4f12-9081-70dcaa20a0da · outbound

This paper cites The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence.

BACON: A fully explainable AI model with graded logic for decision making problems The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence

Reference 4

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unresolved
no resolver link, observed 2026-08-07T15:36:09.274311Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a5fe193e-1848-4005-a8c0-f1e5d94e9243 · outbound

This paper cites Gabbay Artur S.

BACON: A fully explainable AI model with graded logic for decision making problems Gabbay Artur S

Reference 5

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 60856c3c-caea-4d47-a116-a35ef41302f4 · outbound

This paper cites Distilling free-form natural laws from experimental data.

BACON: A fully explainable AI model with graded logic for decision making problems Distilling free-form natural laws from experimental data

Reference 6

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unresolved
no resolver link, observed 2026-08-07T15:36:09.284883Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b0592358-21f4-4337-8adb-bc41c84b6172 · outbound

This paper cites KAN: Kolmogorov-Arnold Networks.

BACON: A fully explainable AI model with graded logic for decision making problems KAN: Kolmogorov-Arnold Networks

Reference 7

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no resolver link, observed 2026-08-07T15:36:09.290246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 62a6d0d0-6623-4329-bae8-d0236b43d78d · outbound

This paper cites Do Two AI Scientists Agree?.

BACON: A fully explainable AI model with graded logic for decision making problems Do Two AI Scientists Agree?

Reference 8

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verified exact
local_arxiv, observed 2026-08-07T15:36:09.705307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation a3694a29-7fb3-41f3-b11d-2841e430a93d · outbound

This paper cites Neural Logic Machines.

BACON: A fully explainable AI model with graded logic for decision making problems Neural Logic Machines

Reference 9

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no resolver link, observed 2026-08-07T15:36:09.299890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 99bc2e87-4935-4e68-b2f0-93170c003ad3 · outbound

This paper cites Soft Computing Evaluation Logic.

BACON: A fully explainable AI model with graded logic for decision making problems Soft Computing Evaluation Logic

Reference 10

Resolution
verified exact
doi, observed 2026-08-07T15:36:09.522922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 584f2ace-0e2f-4515-bdeb-a0ffb0e5b3d8 · outbound

This paper cites Graded logic for decision support systems.

BACON: A fully explainable AI model with graded logic for decision making problems Graded logic for decision support systems

Reference 11

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 5ac01c8e-e644-4dfa-9f0b-a02ad4e4b61a · outbound

This paper cites Graded Logic.

BACON: A fully explainable AI model with graded logic for decision making problems Graded Logic

Reference 12

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 3fb3d7dd-3db2-44bd-9622-2c1d42e6e7d2 · outbound

This paper cites Weighted conjunctive and disjunctive means and their application in system evaluation.

BACON: A fully explainable AI model with graded logic for decision making problems Weighted conjunctive and disjunctive means and their application in system evaluation

Reference 13

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verified fuzzy
raw_fallback, observed 2026-08-07T15:36:10.204457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 5c79f6f8-3b64-48f3-b150-f56258e2de56 · outbound

This paper cites Learning Latent Permutations with Gumbel-Sinkhorn Networks.

BACON: A fully explainable AI model with graded logic for decision making problems Learning Latent Permutations with Gumbel-Sinkhorn Networks

Reference 14

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unresolved
no resolver link, observed 2026-08-07T15:36:09.326328Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e704e0a4-240b-4f91-add8-28ebfc3d987f · outbound

This paper cites an unresolved cited work.

BACON: A fully explainable AI model with graded logic for decision making problems Unresolved cited work

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 080a3242-678c-44b9-acea-d2d076f9e823 · outbound

This paper cites why should i trust you?.

BACON: A fully explainable AI model with graded logic for decision making problems why should i trust you?

Reference 16

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verified fuzzy
raw_fallback, observed 2026-08-07T15:36:10.104354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation d30b1d33-d0ad-40d7-9552-82ee06ca8f6a · outbound

This paper cites A unified approach to interpreting model predictions.

BACON: A fully explainable AI model with graded logic for decision making problems A unified approach to interpreting model predictions

Reference 17

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unresolved
no resolver link, observed 2026-08-07T15:36:09.343128Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation fcfa06f8-6503-4664-b4b0-caef216737cb · outbound

This paper cites Classification and Regression Trees.

BACON: A fully explainable AI model with graded logic for decision making problems Classification and Regression Trees

Reference 18

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation a08dfc13-1191-4949-8e01-81ba20513a11 · outbound

This paper cites Interpretml: A transparent machine learning system.

BACON: A fully explainable AI model with graded logic for decision making problems Interpretml: A transparent machine learning system

Reference 19

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 8d97cdc3-14c0-4ccd-90fa-5239467f848e · outbound

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BACON: A fully explainable AI model with graded logic for decision making problems Unresolved cited work

Reference 20

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 87579337-7f94-4a7c-9da5-e86b300e7b68 · outbound

This paper cites Enhancing breast cancer detection and classification using advanced multi-model features and ensemble machine learning techniques.

BACON: A fully explainable AI model with graded logic for decision making problems Enhancing breast cancer detection and classification using advanced multi-model features and ensemble machine learning techniques

Reference 21

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation f825ea1b-5ac9-4d62-bc26-f806d4e9e2dd · outbound

This paper cites Tumor cell morphology.

BACON: A fully explainable AI model with graded logic for decision making problems Tumor cell morphology

Reference 22

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 67ae19c1-8ad4-4e5a-8dc7-52b912143997 · outbound

This paper cites Accurate breast cancer diagnosis using a stable feature ranking algorithm.

BACON: A fully explainable AI model with graded logic for decision making problems Accurate breast cancer diagnosis using a stable feature ranking algorithm

Reference 23

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 25830884-be2d-454f-9f75-dc6c124aac97 · outbound

This paper cites Boolean algebra.

BACON: A fully explainable AI model with graded logic for decision making problems Boolean algebra

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-07T15:36:09.939521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 8be03015-39e2-4b51-90a2-be2d1276be5d · outbound

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BACON: A fully explainable AI model with graded logic for decision making problems Unresolved cited work

Reference 25

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unresolved
raw_fallback, observed 2026-08-07T15:36:09.910058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation a913d906-d4cf-4267-b10a-325b30983d2f · outbound

This paper cites An Introduction to Statistical Learning: with Applications in R.

BACON: A fully explainable AI model with graded logic for decision making problems An Introduction to Statistical Learning: with Applications in R

Reference 26

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verified fuzzy
raw_fallback, observed 2026-08-07T15:36:09.874924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation e8b7564c-5fc0-433e-bc81-182a0ca9d8ea · outbound

This paper cites Flower classification using supervised learning.

BACON: A fully explainable AI model with graded logic for decision making problems Flower classification using supervised learning

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-07T15:36:09.841790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 4ccd5f99-6571-4b43-966b-f5f94a628293 · outbound

This paper cites Uci machine learning repository: Iris data set.

BACON: A fully explainable AI model with graded logic for decision making problems Uci machine learning repository: Iris data set

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:36:09.812425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 842ec2b0-42f2-40b9-b84b-0e6aa77be1d3 · outbound

This paper cites Usa real estate dataset, 2024.

BACON: A fully explainable AI model with graded logic for decision making problems Usa real estate dataset, 2024

Reference 29

Resolution
verified exact
raw_fallback, observed 2026-08-07T15:36:09.637210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Pith citing papers

No inbound Pith citation observations are available.