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Paper Citation Record · LEDGER

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights

As of 15 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2412.16199.

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

pith.paper-citation-record.v1
2412.16199 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:10:18.448525Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

45 of 45 outbound references displayed

  • verified exact9
  • verified fuzzy6
  • unresolved18
  • parse uncertain0
  • malformed identifier10
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 242e9ef5-7360-414b-bd89-b3ee7a4e7d6e · outbound

This paper cites an unresolved cited work.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Unresolved cited work

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 91808b9f-5739-4fe2-8edb-a15a5b879f07 · outbound

This paper cites Karampuri, S.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Karampuri, S

Reference 2

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source=pdf_text observed=2026-08-11T14:10:18.074807Z digest=sha256:94d0751e77a27ae0b2d4437001d5b50910ad17b79a58c357fe60e8aab0652dae

Observation 7416bfde-7211-44fa-83e9-0bae93fd3c36 · outbound

This paper cites Bhattacharjee, B.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Bhattacharjee, B

Reference 3

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Observation b272c726-0b1a-4aa4-9ee2-85b2f861f77a · outbound

This paper cites an unresolved cited work.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Unresolved cited work

Reference 4

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source=pdf_text observed=2026-08-11T14:10:18.082547Z digest=sha256:b19d9f9bf688e342fa790c45c0e9f950de093e3b7d78a82a7c09d1851a07e497

Observation 737ad784-5269-45c7-a7e7-5ada45987796 · outbound

This paper cites an unresolved cited work.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Unresolved cited work

Reference 5

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source=pdf_text observed=2026-08-11T14:10:18.086618Z digest=sha256:f00b0ac6ea07acf63f6bf7c583e6a11c4a847b52eae778773740d1065e5b50ef

Observation ab3e3a3b-ebc2-4d0a-84aa-e216820d40a0 · outbound

This paper cites Aslam, F.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Aslam, F

Reference 6

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source=pdf_text observed=2026-08-11T14:10:18.090286Z digest=sha256:241cad7332991e684617a7a393c8f26095b95ff97dd3c8c887436833f3671ee8

Observation 4f03aad5-651c-4042-91b2-567374348302 · outbound

This paper cites an unresolved cited work.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Unresolved cited work

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation e71d2daf-e2ae-414b-a77b-723387ec2441 · outbound

This paper cites Magazz, G.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Magazz, G

Reference 8

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source=pdf_text observed=2026-08-11T14:10:18.098918Z digest=sha256:4395a219c16e92f7324d1b22173b3f52a2e286bc41a85cf3440437ecdba48096

Observation 929367ca-c64f-4bda-b615-40c6552b3764 · outbound

This paper cites an unresolved cited work.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Unresolved cited work

Reference 9

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Source-reported events for the cited work

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Observation a212d565-a72c-4cb7-bf20-640e13186a51 · outbound

This paper cites Ball, Is ai leading to a reproducibility crisis in science?, Nature 624 (7990) (2023) 22–25.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Ball, Is ai leading to a reproducibility crisis in science?, Nature 624 (7990) (2023) 22–25

Reference 10

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Observation c9e57d89-7e0c-4dc0-a212-9489043be5f7 · outbound

This paper cites Kapoor, A.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Kapoor, A

Reference 11

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Observation cf923b61-d35f-4635-a174-d04ec9222b7f · outbound

This paper cites Ameli, L.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Ameli, L

Reference 12

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Observation dbbbfd05-d200-4a6b-b73f-950575b7ef28 · outbound

This paper cites Van Noorden, J.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Van Noorden, J

Reference 13

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 7444451f-64f3-4c41-821b-344d20cceb68 · outbound

This paper cites Gunning, D.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Gunning, D

Reference 14

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation dd4a3d3f-90d3-4f48-b785-4636e1da2b86 · outbound

This paper cites Rasheed, A.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Rasheed, A

Reference 15

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Observation 2230f873-674f-4af2-a6e6-110ddf3a1b67 · outbound

This paper cites Nagendran, P.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Nagendran, P

Reference 16

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source=pdf_text observed=2026-08-11T14:10:18.128483Z digest=sha256:c661517f80e709bf27da76edb196baf4c4aab2b1c5a760b2c0f5b3130fea05bc

Observation 233c2751-7afc-495c-9073-dc751ca9be0d · outbound

This paper cites Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI

Reference 17

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Observation 3aed4a99-c0b6-4008-afc0-9f68a830e952 · outbound

This paper cites Futoma, Simons, The lancet digital health jf - the lancet digi- tal health (2020).

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Futoma, Simons, The lancet digital health jf - the lancet digi- tal health (2020)

Reference 18

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation ba58c8c7-55b5-442b-be18-27ac128da12b · outbound

This paper cites an unresolved cited work.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Unresolved cited work

Reference 19

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Observation b7ef7c19-fe35-4be3-ba96-5ce239b81f97 · outbound

This paper cites Chekroud, M.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Chekroud, M

Reference 20

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Observation 1bf0bc7c-dc2f-483c-89b9-5bd9afb4aa16 · outbound

This paper cites an unresolved cited work.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Unresolved cited work

Reference 21

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Observation bbce98ed-0ffc-4236-bd9f-e2b59fec70ad · outbound

This paper cites an unresolved cited work.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Unresolved cited work

Reference 22

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Observation f9b874c1-413c-4dbe-8d6d-2b682e5aa182 · outbound

This paper cites Smith, J.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Smith, J

Reference 23

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Observation d5bf4c3b-b86b-4be9-ace5-0841df50d9c6 · outbound

This paper cites James, D.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights James, D

Reference 24

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Observation 0e4f66a7-2282-4841-aaeb-a929af55e51f · outbound

This paper cites Ezekiel, Methods of correlation analysis (1930).

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Ezekiel, Methods of correlation analysis (1930)

Reference 25

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 802c25c7-5466-4bcc-9a5f-a915826751a1 · outbound

This paper cites Hothorn, A.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Hothorn, A

Reference 26

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation b35013f3-c219-4771-8b92-5f82781488a9 · outbound

This paper cites German, Glass identification (1987).

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights German, Glass identification (1987)

Reference 27

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Observation 8d19818f-d76b-4394-b523-d5e620132530 · outbound

This paper cites Wickham, Dataset: Diamonds (2019).

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Wickham, Dataset: Diamonds (2019)

Reference 28

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Observation 3d67c3cd-b4c5-4df6-9dff-334ddbf5eda7 · outbound

This paper cites Besga, M.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Besga, M

Reference 29

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 587b765e-ccf0-4ef3-b11d-3bce6e24b1ee · outbound

This paper cites URL https://www.R-project.org/.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights URL https://www.R-project.org/

Reference 30

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 85c765bb-05f5-4e07-b8e5-883f964689de · outbound

This paper cites A Unified Approach to Interpreting Model Predictions.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights A Unified Approach to Interpreting Model Predictions

Reference 31

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Observation d0b2dd41-bab2-4b4b-9032-2de10b42cb12 · outbound

This paper cites an unresolved cited work.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Unresolved cited work

Reference 32

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Observation 0d083f06-8c2f-4210-ac05-685cf95fd824 · outbound

This paper cites Breiman, Random forests, Machine Learning 45 (1) (2001) 5–32.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Breiman, Random forests, Machine Learning 45 (1) (2001) 5–32

Reference 33

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Observation c9b33d1b-e96e-4f63-9a02-9fbf621c2e66 · outbound

This paper cites an unresolved cited work.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Unresolved cited work

Reference 34

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Observation 62d1c09a-b367-4aca-a329-243a5b47af33 · outbound

This paper cites Henderson, R.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Henderson, R

Reference 35

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Observation ab261489-7d30-4415-9134-818bdfbe0fe3 · outbound

This paper cites an unresolved cited work.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Unresolved cited work

Reference 36

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Observation a102068e-946c-4178-8820-aa2b4ea61f19 · outbound

This paper cites Besga, I.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Besga, I

Reference 37

Resolution
verified exact
raw_fallback, observed 2026-08-11T14:10:18.746580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 6f3e82cf-1d0a-4a5e-89b2-c41460757703 · outbound

This paper cites an unresolved cited work.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Unresolved cited work

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-11T14:10:18.423317Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:10:18.423317Z digest=sha256:35e6684e2e286c506ffa00eb27ab21fe0ec77ef37b64bfeb92a823d773411a4a

Observation d754bef0-278e-4eae-be0d-7b0f28ef70ec · outbound

This paper cites Kopitar, P.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Kopitar, P

Reference 39

Resolution
malformed identifier
raw_fallback, observed 2026-08-11T14:10:20.136517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T14:10:18.426690Z digest=sha256:8c9fa1fb112ac8044831b7624f66c5cfcf2c1eced577ad6e63202c6ee3d1bad5

Observation e802f26f-b6b8-4e9c-97f5-165938955ce8 · outbound

This paper cites an unresolved cited work.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Unresolved cited work

Reference 40

Resolution
verified exact
doi, observed 2026-08-11T14:10:18.516008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T14:10:18.429890Z digest=sha256:a94f70bf79b2d24b34031b9817b86270909a5dde3ce52ceef45e0af760080adf

Observation 30a50548-a411-4610-a4a7-95bba3744018 · outbound

This paper cites Bzdok, M.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Bzdok, M

Reference 41

Resolution
verified exact
doi, observed 2026-08-11T14:10:18.505057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T14:10:18.433235Z digest=sha256:eca2a77c065e1f0d680bd6c5017483ff85f9978ea73e747c80bc2dd60c1d6fde

Observation 5e24b649-9550-4214-8d95-81d5009cf087 · outbound

This paper cites Obermeyer, E.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Obermeyer, E

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-11T14:10:18.437513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:10:18.437513Z digest=sha256:1b847fa1fd0721c67094a3ea965798ba5fa0b1ef863d455a27d539236a3ea204

Observation 1b0dadb6-ca70-40c1-ba5b-1d2af9f05c41 · outbound

This paper cites Bouthillier, C.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Bouthillier, C

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:10:20.124518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T14:10:18.440905Z digest=sha256:309d3fd3187cb11d3ca9fab2fe9c037a128b97bd1bb75484bffc8faa1362b151

Observation faa871ad-4695-4e68-99ac-63d830d2f430 · outbound

This paper cites Ciobanu-Caraus, A.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Ciobanu-Caraus, A

Reference 44

Resolution
verified exact
doi, observed 2026-08-11T14:10:18.488119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T14:10:18.444003Z digest=sha256:514b57f01a565a66b8e729aa853b15ce9159a2c17b496580db9ee452452cc546

Observation 8acb7c77-9698-4efd-b9c1-b9377830baf6 · outbound

This paper cites an unresolved cited work.

Stabilizing Machine Learning for Reproducible and Explainable Results: A Novel Validation Approach to Subject-Specific Insights Unresolved cited work

Reference 45

Resolution
verified exact
doi, observed 2026-08-11T14:10:18.477884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T14:10:18.448525Z digest=sha256:010fd050a2e53e615cad43f95011d8f0d6d6ea73a9c74eff3aa30358fa5e5269

Pith citing papers

No inbound Pith citation observations are available.