Paper Citation Record · LEDGER

Estimating Probabilities of Causation with Machine Learning Models

As of 22 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 2026-08-21T06:32:19.484+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
malformed identifier0
metadata mismatch0

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:32:56.152800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:32:56.141119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: verified fuzzy; 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 2026-08-21T06:32:19.484+00:00.

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

This paper cites Friedman.

Estimating Probabilities of Causation with Machine Learning Models Friedman

Reference 5

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: 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 2026-08-21T06:32:19.484+00:00.

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

Resolution: verified fuzzy; 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 2026-08-21T06:32:19.484+00:00.

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

Resolution: verified fuzzy; 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 2026-08-21T06:32:19.484+00:00.

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

Resolution: verified fuzzy; 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 2026-08-21T06:32:19.484+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: verified fuzzy; 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 2026-08-21T06:32:19.484+00:00.

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

Resolution: verified fuzzy; 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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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

Resolution: verified fuzzy; 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 2026-08-21T06:32:19.484+00:00.

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

Resolution: verified fuzzy; 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 2026-08-21T06:32:19.484+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: verified fuzzy; 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 2026-08-21T06:32:19.484+00:00.

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

Resolution: verified fuzzy; 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 2026-08-21T06:32:19.484+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-21T06:32:19.484+00:00.

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

Resolution: verified fuzzy; 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 2026-08-21T06:32:19.484+00:00.

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

Resolution: verified fuzzy; 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 2026-08-21T06:32:19.484+00:00.

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: verified fuzzy; 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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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.

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.

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 2026-08-21T06:32:19.484+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-21T06:32:19.484+00:00.

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

Resolution: verified exact; 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 2026-08-21T06:32:19.484+00:00.