Paper Citation Record · LEDGER

Design-based edge-level causal inference with machine learning assisted covariate adjustment

As of 12 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2606.00965.

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

pith.paper-citation-record.v1
2606.00965 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-28T17:04:43.856708Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

35 of 35 outbound references displayed

verified exact7
verified fuzzy0
unresolved28
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5dc9405b-7b77-489c-bb18-904ba0178cd0 · outbound

This paper cites an unresolved cited work.

Design-based edge-level causal inference with machine learning assisted covariate adjustment Unresolved cited work

Reference 1

Resolution: unresolved; no resolver link, observed 2026-06-28T17:04:43.856708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 343a6453-8167-4868-9a2c-3c66ba117d25 · outbound

This paper cites an unresolved cited work.

Design-based edge-level causal inference with machine learning assisted covariate adjustment Unresolved cited work

Reference 2

Resolution: unresolved; no resolver link, observed 2026-06-28T17:04:43.856708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0330440c-77f9-403a-8d03-87a8a40cc71c · outbound

This paper cites an unresolved cited work.

Design-based edge-level causal inference with machine learning assisted covariate adjustment Unresolved cited work

Reference 3

Resolution: unresolved; no resolver link, observed 2026-06-28T17:04:43.856708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 740fd072-29c5-4639-b9ce-b79594e90f37 · outbound

This paper cites & Aronow, P.

Design-based edge-level causal inference with machine learning assisted covariate adjustment & Aronow, P

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-28T17:04:43.856708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd437083-4a19-448a-afdb-c770ce2aa274 · outbound

This paper cites an unresolved cited work.

Design-based edge-level causal inference with machine learning assisted covariate adjustment Unresolved cited work

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-28T17:04:43.856708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a31a8307-9890-46d2-a4ca-5353b6b083b5 · outbound

This paper cites an unresolved cited work.

Design-based edge-level causal inference with machine learning assisted covariate adjustment Unresolved cited work

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-28T17:04:43.856708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c59225fc-40c5-415e-905e-91cf17f72cc9 · outbound

This paper cites Unbiased Estimation for Total Treatment Effect Under Interference Using Aggregated Dyadic Data.

Design-based edge-level causal inference with machine learning assisted covariate adjustment Unbiased Estimation for Total Treatment Effect Under Interference Using Aggregated Dyadic Data

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-07-01T21:26:14.242916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 90aa1f66-1bb3-41ce-a1c8-7cf7d09b34a8 · outbound

This paper cites it’s always about the people. enron is no different.

Design-based edge-level causal inference with machine learning assisted covariate adjustment it’s always about the people. enron is no different

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-28T17:04:43.856708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f1e773fd-1d1a-4ba5-99cb-01a2893b6301 · outbound

This paper cites (2024),A First Course in Causal Inference, CRC Press.

Design-based edge-level causal inference with machine learning assisted covariate adjustment (2024),A First Course in Causal Inference, CRC Press

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-28T17:04:43.856708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22514b0d-d1db-42c9-85e8-b30b16c73acf · outbound

This paper cites an unresolved cited work.

Design-based edge-level causal inference with machine learning assisted covariate adjustment Unresolved cited work

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-28T17:04:43.856708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6704c091-5e38-4e41-a0dd-b4f4ce3db4ca · outbound

This paper cites & Basse, G.

Design-based edge-level causal inference with machine learning assisted covariate adjustment & Basse, G

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-28T17:04:43.856708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33c4d322-d048-47e9-9e54-0406d842ab1c · outbound

This paper cites an unresolved cited work.

Design-based edge-level causal inference with machine learning assisted covariate adjustment Unresolved cited work

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-28T17:04:43.856708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 840357a0-e93c-43d7-a285-2e3ce9f3b2f7 · outbound

This paper cites an unresolved cited work.

Design-based edge-level causal inference with machine learning assisted covariate adjustment Unresolved cited work

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-28T17:04:43.856708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47dbf88e-d6f6-41d0-8ddf-6d4c8a324766 · outbound

This paper cites an unresolved cited work.

Design-based edge-level causal inference with machine learning assisted covariate adjustment Unresolved cited work

Reference 14

Resolution: unresolved; no resolver link, observed 2026-06-28T17:04:43.856708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e18b70c-b677-49a3-89bf-a190efdad9e1 · outbound

This paper cites (2023), ‘High-dimensional central limit theorems for homogeneous sums’,Journal of Theoretical Probability36(1), 1–45.

Design-based edge-level causal inference with machine learning assisted covariate adjustment (2023), ‘High-dimensional central limit theorems for homogeneous sums’,Journal of Theoretical Probability36(1), 1–45

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-28T17:04:43.856708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf52c889-7523-447e-98c4-2eac45946a35 · outbound

This paper cites & Ding, P.

Design-based edge-level causal inference with machine learning assisted covariate adjustment & Ding, P

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-28T17:04:43.856708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f432ef9d-0a1e-4f08-a530-4460c4879e3f · outbound

This paper cites an unresolved cited work.

Design-based edge-level causal inference with machine learning assisted covariate adjustment Unresolved cited work

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-28T17:04:43.856708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c6611bd-aa36-4bac-a7ce-5c1d58df4c53 · outbound

This paper cites & Wager, S.

Design-based edge-level causal inference with machine learning assisted covariate adjustment & Wager, S

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-28T17:04:43.856708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98077eea-8e5e-4904-9567-1e77981a443c · outbound

This paper cites Causal inference with dyadic data in randomized experiments.

Design-based edge-level causal inference with machine learning assisted covariate adjustment Causal inference with dyadic data in randomized experiments

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-07-01T21:26:14.259756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 34fdac85-ad3a-4c5e-a22a-e03d1a1b128b · outbound

This paper cites (2013), ‘Agnostic notes on regression adjustments to experimental data: Reexam- ining freedman’s critique’,The Annals of Applied Statistics7(1), 295–318.

Design-based edge-level causal inference with machine learning assisted covariate adjustment (2013), ‘Agnostic notes on regression adjustments to experimental data: Reexam- ining freedman’s critique’,The Annals of Applied Statistics7(1), 295–318

Reference 20

Resolution: unresolved; no resolver link, observed 2026-06-28T17:04:43.856708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aab64f13-8997-45ab-8bca-43dfffacb03c · outbound

This paper cites & Yang, Y.

Design-based edge-level causal inference with machine learning assisted covariate adjustment & Yang, Y

Reference 21

Resolution: unresolved; no resolver link, observed 2026-06-28T17:04:43.856708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b97caa3b-b49f-4b6e-84c0-0eb63f1de8e7 · outbound

This paper cites & Hudgens, M.

Design-based edge-level causal inference with machine learning assisted covariate adjustment & Hudgens, M

Reference 22

Resolution: unresolved; no resolver link, observed 2026-06-28T17:04:43.856708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0ff8ddd-5271-40d8-bce1-ed9e54502500 · outbound

This paper cites & Liu, H.

Design-based edge-level causal inference with machine learning assisted covariate adjustment & Liu, H

Reference 23

Resolution: unresolved; no resolver link, observed 2026-06-28T17:04:43.856708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 83a6193e-52bd-4f78-a2ef-862cb7b2d8ce · outbound

This paper cites Conditional cross-fitting for unbiased machine-learning-assisted covariate adjustment in randomized experiments.

Design-based edge-level causal inference with machine learning assisted covariate adjustment Conditional cross-fitting for unbiased machine-learning-assisted covariate adjustment in randomized experiments

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-07-01T21:26:14.256604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9c8f326f-a3e4-4c96-a2af-b2a914658db0 · outbound

This paper cites & Wang, Y.

Design-based edge-level causal inference with machine learning assisted covariate adjustment & Wang, Y

Reference 25

Resolution: unresolved; no resolver link, observed 2026-06-28T17:04:43.856708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a6460bd-f036-4124-9126-62a3c9775ff4 · outbound

This paper cites Dyadic data with ordered outcome variables.

Design-based edge-level causal inference with machine learning assisted covariate adjustment Dyadic data with ordered outcome variables

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-07-01T21:26:14.253403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e5bc0c4d-fed8-4cdf-9532-c1a4e0a0d659 · outbound

This paper cites (1923), ‘On the application of probability theory to agricultural experiments.

Design-based edge-level causal inference with machine learning assisted covariate adjustment (1923), ‘On the application of probability theory to agricultural experiments

Reference 27

Resolution: unresolved; no resolver link, observed 2026-06-28T17:04:43.856708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f8b91f2-4d13-4ee9-9378-97033ce58ef6 · outbound

This paper cites an unresolved cited work.

Design-based edge-level causal inference with machine learning assisted covariate adjustment Unresolved cited work

Reference 28

Resolution: unresolved; no resolver link, observed 2026-06-28T17:04:43.856708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a84e448-732b-4791-8c49-2bacd58edd8c · outbound

This paper cites an unresolved cited work.

Design-based edge-level causal inference with machine learning assisted covariate adjustment Unresolved cited work

Reference 29

Resolution: unresolved; no resolver link, observed 2026-06-28T17:04:43.856708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 723068ff-703f-4d82-9f78-89a63cfe0913 · outbound

This paper cites Asymptotic theory of the quadratic assignment procedure for dyadic data analysis.

Design-based edge-level causal inference with machine learning assisted covariate adjustment Asymptotic theory of the quadratic assignment procedure for dyadic data analysis

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-07-01T21:26:14.245681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8b40b379-9911-4a4b-a9f4-5f04b62798be · outbound

This paper cites A decorrelation method for general regression adjustment in randomized experiments.

Design-based edge-level causal inference with machine learning assisted covariate adjustment A decorrelation method for general regression adjustment in randomized experiments

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-07-01T21:26:14.250847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8ad4912e-102f-4490-9106-41feec8bbd4a · outbound

This paper cites Elements of estimation theory for causal effects in the presence of network interference.

Design-based edge-level causal inference with machine learning assisted covariate adjustment Elements of estimation theory for causal effects in the presence of network interference

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-07-01T21:26:14.248234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 67582e23-ea54-4cd1-a2af-12d739a71625 · outbound

This paper cites an unresolved cited work.

Design-based edge-level causal inference with machine learning assisted covariate adjustment Unresolved cited work

Reference 33

Resolution: unresolved; no resolver link, observed 2026-06-28T17:04:43.856708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0593cf32-6fc2-4f87-8e52-368025fabec6 · outbound

This paper cites L., Airoldi, E.

Design-based edge-level causal inference with machine learning assisted covariate adjustment L., Airoldi, E

Reference 34

Resolution: unresolved; no resolver link, observed 2026-06-28T17:04:43.856708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation de548cca-9129-44aa-85a9-a960ad5e3a44 · outbound

This paper cites an unresolved cited work.

Design-based edge-level causal inference with machine learning assisted covariate adjustment Unresolved cited work

Reference 35

Resolution: unresolved; no resolver link, observed 2026-06-28T17:04:43.856708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.