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Paper Citation Record · LEDGER

Estimating Probabilities of Causation with Machine Learning Models

As of 8 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 1 inbound Pith citation observation for arXiv:2502.08858.

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

pith.paper-citation-record.v1
2502.08858 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T23:32:55.700215Z

measured 33 of 33 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-11T01:39:50.275352Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-11T01:40:51.683464Z

Reference resolution

32 of 32 outbound references displayed

  • verified exact0
  • verified fuzzy23
  • unresolved9
  • parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d04a81eb-a610-4ff6-8d9c-419936433512 · outbound

This paper cites Probabilistic counterfactuals: semantics, computation, and applications.

Estimating Probabilities of Causation with Machine Learning Models Probabilistic counterfactuals: semantics, computation, and applications

Reference 1

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Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-07T23:32:55.589713Z digest=sha256:48c9ad2b8b8eaeb11ae146e5ed99beddd4f13e4bc491b66a8c5a37e48f15bc0b

Observation 5d6eafe5-2c38-433b-a406-3877f5f37028 · outbound

This paper cites Random search for hyper-parameter optimization.

Estimating Probabilities of Causation with Machine Learning Models Random search for hyper-parameter optimization

Reference 2

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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.

source=arxiv_source observed=2026-08-07T23:32:55.594045Z digest=sha256:ced5253317549d88b1256a6d8473ef569349b67ca73b60e3deadb45971a590e3

Observation 02839eb3-acba-4653-97fe-b256c0cfc7d5 · outbound

This paper cites Support-vector networks.

Estimating Probabilities of Causation with Machine Learning Models Support-vector networks

Reference 3

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no resolver link, observed 2026-08-07T23:32:55.597844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T23:32:55.597844Z digest=sha256:aa192f32d60e6b907e42634598e129954a05caaf6f7d18a0e6d39475b7281882

Observation 946d25e4-cc2c-4fb4-9336-64c3ab89e267 · outbound

This paper cites The probability of causation.

Estimating Probabilities of Causation with Machine Learning Models The probability of causation

Reference 4

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raw_fallback, observed 2026-08-07T23:32:56.121925Z

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.

source=arxiv_source observed=2026-08-07T23:32:55.601869Z digest=sha256:0694aff44a9ebdd23f4224a6b949b105baae29d0ef1baaa59f730c2d8eeacf7a

Observation e63dfaee-8399-4afd-b8a5-589618094b29 · outbound

This paper cites Friedman.

Estimating Probabilities of Causation with Machine Learning Models Friedman

Reference 5

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unresolved
no resolver link, observed 2026-08-07T23:32:55.605591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T23:32:55.605591Z digest=sha256:cd1eaf3a597fb7de3341575a3aea5b379e331ee8dad6def699221bc0b4b68278

Observation 8f8a5cb4-4993-4583-92ef-d022201b4780 · outbound

This paper cites An axiomatic characterization of causal counterfactuals.

Estimating Probabilities of Causation with Machine Learning Models An axiomatic characterization of causal counterfactuals

Reference 6

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verified fuzzy
raw_fallback, observed 2026-08-07T23:32:56.110794Z

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.

source=arxiv_source observed=2026-08-07T23:32:55.609513Z digest=sha256:1a16dc95638ff1d576cd35ddccb40d21510cede9da222fe9cdc6826c0b88beb8

Observation 35d0ec88-c2c3-42ba-af02-100cb1ca2151 · outbound

This paper cites Axiomatizing causal reasoning.

Estimating Probabilities of Causation with Machine Learning Models Axiomatizing causal reasoning

Reference 7

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raw_fallback, observed 2026-08-07T23:32:56.099848Z

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.

source=arxiv_source observed=2026-08-07T23:32:55.613631Z digest=sha256:352ff82531f8fd59f6ecdecc5a09d06315af02c4d606ccd09d6dd371b298828c

Observation 5a564768-76a2-4375-90f9-c564c892b139 · outbound

This paper cites Causal analysis after haavelmo.

Estimating Probabilities of Causation with Machine Learning Models Causal analysis after haavelmo

Reference 8

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raw_fallback, observed 2026-08-07T23:32:56.088830Z

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.

source=arxiv_source observed=2026-08-07T23:32:55.617138Z digest=sha256:d31dfee8d241bf8e48d307305cf0e7cbfab565af83dc4ba8b16682c5e3745ad0

Observation 0a3de745-3c00-4567-94b7-0559f6e33a59 · outbound

This paper cites Random decision forests.

Estimating Probabilities of Causation with Machine Learning Models Random decision forests

Reference 9

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raw_fallback, observed 2026-08-07T23:32:56.077151Z

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.

source=arxiv_source observed=2026-08-07T23:32:55.620556Z digest=sha256:7f4483b1b5f810443f92531df6634e1fa913a449d3ca4573629bc2a7333fa7ab

Observation b9be32a1-e3a8-4f43-9eb1-d3ba30af6c63 · outbound

This paper cites Causal inference in statistics, social, and biomedical sciences.

Estimating Probabilities of Causation with Machine Learning Models Causal inference in statistics, social, and biomedical sciences

Reference 10

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no resolver link, observed 2026-08-07T23:32:55.623871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T23:32:55.623871Z digest=sha256:d0b1b4eaa7e296bcaafe2a323596e2ea08cf929581c638a214a3117e6df47abd

Observation a60387de-82b6-4d62-b936-627971a02b18 · outbound

This paper cites Unit selection based on counterfactual logic.

Estimating Probabilities of Causation with Machine Learning Models Unit selection based on counterfactual logic

Reference 11

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raw_fallback, observed 2026-08-07T23:32:56.058097Z

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.

source=arxiv_source observed=2026-08-07T23:32:55.627082Z digest=sha256:22545a89a0a5d0ebfca7e700124cf8d9aa4ed52cb9ba7d21a17b4577f50ef521

Observation f54c74a2-82b6-4927-b1c8-ce0a8c5bf324 · outbound

This paper cites Probabilities of causation: Role of observational data.

Estimating Probabilities of Causation with Machine Learning Models Probabilities of causation: Role of observational data

Reference 12

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raw_fallback, observed 2026-08-07T23:32:56.047006Z

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.

source=arxiv_source observed=2026-08-07T23:32:55.630614Z digest=sha256:1d3fd41d01f22bdc47fedba6d251af9b449213297c8a9045440ae80ca1060c58

Observation e1735b38-c14c-40fe-8b97-0456a99659d1 · outbound

This paper cites Probabilities of causation with nonbinary treatment and effect.

Estimating Probabilities of Causation with Machine Learning Models Probabilities of causation with nonbinary treatment and effect

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T23:32:56.035302Z

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.

source=arxiv_source observed=2026-08-07T23:32:55.634149Z digest=sha256:953d61d833cd21c45c5b027335dc710b0b314430d6532871f0751ccf75bea2ee

Observation 4ef20655-3ada-447f-9ce9-830ba835d6c9 · outbound

This paper cites Unit selection with nonbinary treatment and effect.

Estimating Probabilities of Causation with Machine Learning Models Unit selection with nonbinary treatment and effect

Reference 14

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raw_fallback, observed 2026-08-07T23:32:56.023226Z

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.

source=arxiv_source observed=2026-08-07T23:32:55.637665Z digest=sha256:cdd4daad281e9ea8f5d87065a1a1531178a1ebaecf759d95954cfc5fb74ee014

Observation 4839ca54-01fc-4b7e-b179-cf2afc222aee · outbound

This paper cites Chen, Jingzheng Qin, and Zhen Qin.

Estimating Probabilities of Causation with Machine Learning Models Chen, Jingzheng Qin, and Zhen Qin

Reference 15

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raw_fallback, observed 2026-08-07T23:32:56.011339Z

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.

source=arxiv_source observed=2026-08-07T23:32:55.640902Z digest=sha256:72f77003ce661d8e32e10addb2ee1b3ca36398e7be2773fa3266a357cb3269bc

Observation ee8c0328-780c-4e8d-b381-436f93f9580c · outbound

This paper cites Learning Probabilities of Causation from Finite Population Data.

Estimating Probabilities of Causation with Machine Learning Models Learning Probabilities of Causation from Finite Population Data

Reference 16

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unresolved
no resolver link, observed 2026-08-07T23:32:55.644341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T23:32:55.644341Z digest=sha256:49a05000d94c571ffd88662850fc2317e777828626ba3dbe075ff91afd099360

Observation 0942ef7c-e35a-4b9b-8587-c8df019d7aff · outbound

This paper cites Unit selection: Learning benefit function from finite population data.

Estimating Probabilities of Causation with Machine Learning Models Unit selection: Learning benefit function from finite population data

Reference 17

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raw_fallback, observed 2026-08-07T23:32:55.999676Z

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.

source=arxiv_source observed=2026-08-07T23:32:55.648136Z digest=sha256:eb6fc6d2bd7729692a7dbad5602d51548373172580c0823c3c025acd24a1c2ca

Observation 33b61e5c-7650-467b-8909-55c3b1c35782 · outbound

This paper cites Probabilities of causation: Adequate size of experimental and observational samples.

Estimating Probabilities of Causation with Machine Learning Models Probabilities of causation: Adequate size of experimental and observational samples

Reference 18

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raw_fallback, observed 2026-08-07T23:32:55.988041Z

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.

source=arxiv_source observed=2026-08-07T23:32:55.651779Z digest=sha256:7bb90144bc01596820e46f8b1e3bab87110c5ec07705bc6ef0d0be1f0703b114

Observation d7f4a89c-bcf9-436b-8565-227b555f1504 · outbound

This paper cites Rectifier nonlinearities improve neural network acoustic models.

Estimating Probabilities of Causation with Machine Learning Models Rectifier nonlinearities improve neural network acoustic models

Reference 19

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no resolver link, observed 2026-08-07T23:32:55.655174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T23:32:55.655174Z digest=sha256:bea90f9bcec9107bb0f05ac2865fc97069fe4235ef47a599b8a649d81ee729b7

Observation cfe4bc50-daeb-4a50-ab88-a0b5466b851c · outbound

This paper cites Mish: A Self Regularized Non-Monotonic Activation Function.

Estimating Probabilities of Causation with Machine Learning Models Mish: A Self Regularized Non-Monotonic Activation Function

Reference 20

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no resolver link, observed 2026-08-07T23:32:55.658655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T23:32:55.658655Z digest=sha256:df6c891914c8143266d13200ba7165c524cabc57eaadead983ed7f18b69166a2

Observation 7484c896-dfc0-4a2b-8599-f804153c9a74 · outbound

This paper cites Perspective on `harm' in personalized medicine -- an alternative perspective.

Estimating Probabilities of Causation with Machine Learning Models Perspective on `harm' in personalized medicine -- an alternative perspective

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T23:32:55.969648Z

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.

source=arxiv_source observed=2026-08-07T23:32:55.662471Z digest=sha256:fb62b5b7b92012b05f912c349db06c5147a3717868f219778cb8883ef31f53f3

Observation ca4fac38-38d1-4c71-84b9-06668b8fca56 · outbound

This paper cites Causes of effects: Learning individual responses from population data.

Estimating Probabilities of Causation with Machine Learning Models Causes of effects: Learning individual responses from population data

Reference 22

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raw_fallback, observed 2026-08-07T23:32:55.958373Z

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.

source=arxiv_source observed=2026-08-07T23:32:55.665802Z digest=sha256:37f5931e489e218580b32cd23790ba8cb0fc05c93a046e95c83589809c5fb5f8

Observation 586ad258-937f-4209-88c9-2ff12f36ab67 · outbound

This paper cites Rectified linear units improve restricted boltzmann machines.

Estimating Probabilities of Causation with Machine Learning Models Rectified linear units improve restricted boltzmann machines

Reference 23

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raw_fallback, observed 2026-08-07T23:32:55.946847Z

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.

source=arxiv_source observed=2026-08-07T23:32:55.669073Z digest=sha256:7c3f80e81f41bbb94642c8e071fd1bc106557150b2d915a147762ed7e2f68e31

Observation ec3a40f5-f2c8-4043-9342-8df8ac771d38 · outbound

This paper cites Aspects of graphical models connected with causality.

Estimating Probabilities of Causation with Machine Learning Models Aspects of graphical models connected with causality

Reference 24

Resolution
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raw_fallback, observed 2026-08-07T23:32:55.933963Z

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.

source=arxiv_source observed=2026-08-07T23:32:55.672334Z digest=sha256:174fb4d065b574a4da31953d7c927a3687b357c86c0d367658916abbfc161d5e

Observation 062ceca2-d4f3-48f9-9169-6a01a43b547f · outbound

This paper cites Causal diagrams for empirical research.

Estimating Probabilities of Causation with Machine Learning Models Causal diagrams for empirical research

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T23:32:55.922847Z

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.

source=arxiv_source observed=2026-08-07T23:32:55.675900Z digest=sha256:745f9883df34a959dcea2a53d861710e784337f8ec625a28276cdeea0c50e724

Observation 97bf9774-7856-43e0-adc8-fff210eba020 · outbound

This paper cites Probabilities of causation: Three counterfactual interpretations and their identification.

Estimating Probabilities of Causation with Machine Learning Models Probabilities of causation: Three counterfactual interpretations and their identification

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T23:32:55.911470Z

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.

source=arxiv_source observed=2026-08-07T23:32:55.679340Z digest=sha256:3b83274e6ad8acaf30b1eac5e8fadfef037c4423ce484a10c73581c499863713

Observation b3d0f9d2-11bb-4de4-a2be-9c597b1527ec · outbound

This paper cites Causality.

Estimating Probabilities of Causation with Machine Learning Models Causality

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T23:32:55.899679Z

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.

source=arxiv_source observed=2026-08-07T23:32:55.682828Z digest=sha256:acaa93860743edc76d7c08a7f422d992cd7874c63e8070a2b601a48f85cd79fb

Observation 90d8e8a7-6ba2-431d-a704-4ccfc1290a65 · outbound

This paper cites Causal Fairness Analysis.

Estimating Probabilities of Causation with Machine Learning Models Causal Fairness Analysis

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T23:32:55.686521Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T23:32:55.686521Z digest=sha256:5f03b766ebff75dc513687b90ba0b3d2d213db1b2156c4ee972a54ca72544ce7

Observation af0aaf77-5d06-4c0f-a822-237011e6f6c3 · outbound

This paper cites Rumelhart, Geoffrey E.

Estimating Probabilities of Causation with Machine Learning Models Rumelhart, Geoffrey E

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T23:32:55.690200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T23:32:55.690200Z digest=sha256:10bc4ef2760ca4d8894b2b1512b1d954fee81a725b2d04ad8eadc1707a0b7b89

Observation ad164cf5-1dde-411c-8218-a0f5f8edeb81 · outbound

This paper cites Probabilities of causation: Bounds and identification.

Estimating Probabilities of Causation with Machine Learning Models Probabilities of causation: Bounds and identification

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T23:32:55.888414Z

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.

source=arxiv_source observed=2026-08-07T23:32:55.693495Z digest=sha256:6a69a0a5a21b45a2d46db15c8e8f9be8d5034d7b72b6697cd019dc15fe1a99e5

Observation 1e667230-8ff3-4d80-a815-1907099b711d · outbound

This paper cites Attention is all you need.

Estimating Probabilities of Causation with Machine Learning Models Attention is all you need

Reference 31

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unresolved
no resolver link, observed 2026-08-07T23:32:55.696749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T23:32:55.696749Z digest=sha256:1600924599dea46a5fdc87bcfe1276f4c709a9c301c3d39dc4052fb914da80c7

Observation f9ce8791-2f65-44f7-a825-ec3a4effc8ca · outbound

This paper cites Causal ai framework for unit selection in optimizing electric vehicle procurement.

Estimating Probabilities of Causation with Machine Learning Models Causal ai framework for unit selection in optimizing electric vehicle procurement

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T23:32:55.869464Z

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.

source=arxiv_source observed=2026-08-07T23:32:55.700215Z digest=sha256:af362830fea9c3f28198f511044d3dcf4908020c273d070c883cf2e8c8d55e17

Pith citing papers

Observation c9680a1f-b0d0-43c3-94c7-9c63763b88f6 · inbound

Causal EpiNets: Precision-corrected Bounds on Individual Treatment Effects using Epistemic Neural Networks cites this paper.

Causal EpiNets: Precision-corrected Bounds on Individual Treatment Effects using Epistemic Neural Networks Estimating Probabilities of Causation with Machine Learning Models

Reference 49

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arxiv_id, observed 2026-05-11T01:40:51.685120Z

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.

source=arxiv_source observed=2026-05-11T01:39:50.275352Z digest=sha256:f1b583e9c7bfe196beed99c9a44e8e9ebbde4809b09af996bb7d875395f413dd