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Paper Citation Record · LEDGER

Constructing targeted minimum loss/maximum likelihood estimators: a simple illustration to build intuition

As of 17 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2507.11680.

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

pith.paper-citation-record.v1
2507.11680 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:12:30.964221Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

18 of 18 outbound references displayed

  • verified exact5
  • verified fuzzy6
  • unresolved5
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 390b864b-5ebd-493c-b35f-a3c78481356c · outbound

This paper cites A Targeted Maximum Likelihood Estimator of a Causal Effect on a Bounded Continuous Outcome.

Constructing targeted minimum loss/maximum likelihood estimators: a simple illustration to build intuition A Targeted Maximum Likelihood Estimator of a Causal Effect on a Bounded Continuous Outcome

Reference 1

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Source-reported events for the cited work

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Observation 8b2f6724-ada7-4c0a-a6e4-7260dbb0b124 · outbound

This paper cites Demystifying statistical learning based on efficient influence functions.

Constructing targeted minimum loss/maximum likelihood estimators: a simple illustration to build intuition Demystifying statistical learning based on efficient influence functions

Reference 2

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verified exact
local_arxiv, observed 2026-08-06T17:12:32.318415Z

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Observation 8f3b30ad-c1ef-458d-9002-16756825a999 · outbound

This paper cites Demystifying Double Robustness: A Comparison of Alterna- tive Strategies for Estimating a Population Mean from Incomplete Data.

Constructing targeted minimum loss/maximum likelihood estimators: a simple illustration to build intuition Demystifying Double Robustness: A Comparison of Alterna- tive Strategies for Estimating a Population Mean from Incomplete Data

Reference 3

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verified exact
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Observation 2e65f810-6bd1-4fb2-830f-b748082603f7 · outbound

This paper cites Semiparametric theory and empirical processes in causal inference.

Constructing targeted minimum loss/maximum likelihood estimators: a simple illustration to build intuition Semiparametric theory and empirical processes in causal inference

Reference 4

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Source-reported events for the cited work

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Observation 80d912f9-81ac-4d1e-ad72-d9754e9db9f7 · outbound

This paper cites Semiparametric doubly robust targeted double machine learning: a review.

Constructing targeted minimum loss/maximum likelihood estimators: a simple illustration to build intuition Semiparametric doubly robust targeted double machine learning: a review

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 83d3be50-02ec-4b75-ad14-9d6dcf59fe7c · outbound

This paper cites Pulling back the curtain: the road from statistical estimand to machine-learning based estimator for epidemiologists (no wizard required).

Constructing targeted minimum loss/maximum likelihood estimators: a simple illustration to build intuition Pulling back the curtain: the road from statistical estimand to machine-learning based estimator for epidemiologists (no wizard required)

Reference 6

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verified exact
local_arxiv, observed 2026-08-06T17:12:31.316664Z

Source-reported events for the cited work

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Observation 23b99573-e471-4cbb-90a9-c639262f992d · outbound

This paper cites Comment: Performance of Double-Robust Estimators When ``Inverse Probability'' Weights Are Highly Variable.

Constructing targeted minimum loss/maximum likelihood estimators: a simple illustration to build intuition Comment: Performance of Double-Robust Estimators When ``Inverse Probability'' Weights Are Highly Variable

Reference 7

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local_arxiv, observed 2026-08-06T17:12:31.814533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation be5d13d2-2f3d-4597-910a-244e326a33a1 · outbound

This paper cites Targeted maximum likelihood estimation for causal inference in observational studies.

Constructing targeted minimum loss/maximum likelihood estimators: a simple illustration to build intuition Targeted maximum likelihood estimation for causal inference in observational studies

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d2fddc12-c327-490c-934e-1e80daf9d0c3 · outbound

This paper cites Targeted Maximum Likelihood Based Causal Inference: Part II.

Constructing targeted minimum loss/maximum likelihood estimators: a simple illustration to build intuition Targeted Maximum Likelihood Based Causal Inference: Part II

Reference 9

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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 2026-08-17T06:30:58.91139+00:00.

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Observation d5897811-f7f8-467f-a9bc-4b33dbb1f8d4 · outbound

This paper cites Van Der Laan and Sherri Rose.Targeted learning: causal inference for observational and experi- mental data.

Constructing targeted minimum loss/maximum likelihood estimators: a simple illustration to build intuition Van Der Laan and Sherri Rose.Targeted learning: causal inference for observational and experi- mental data

Reference 10

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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 2026-08-17T06:30:58.91139+00:00.

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Observation d071a28c-66b3-4f78-81b9-fc514433b617 · outbound

This paper cites Targeted Maximum Likelihood Learning.

Constructing targeted minimum loss/maximum likelihood estimators: a simple illustration to build intuition Targeted Maximum Likelihood Learning

Reference 11

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Source-reported events for the cited work

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Observation 0c7697ca-c714-405c-8708-f4be44226b1a · outbound

This paper cites Analysis of incomplete data using inverse probability weighting and doubly robust estimators.

Constructing targeted minimum loss/maximum likelihood estimators: a simple illustration to build intuition Analysis of incomplete data using inverse probability weighting and doubly robust estimators

Reference 12

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verified exact
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Observation 08cd3248-d6c6-4858-9e71-783c2af5a543 · outbound

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Constructing targeted minimum loss/maximum likelihood estimators: a simple illustration to build intuition Unresolved cited work

Reference 13

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Observation 361eea49-e815-4685-8c90-94ed42efc9e0 · outbound

This paper cites Predictions from this model arebµ.

Constructing targeted minimum loss/maximum likelihood estimators: a simple illustration to build intuition Predictions from this model arebµ

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-06T17:12:33.448429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 7ebc7072-981e-4b47-bc91-8224a3a1152e · outbound

This paper cites Predictions from this model arebµ ∗.

Constructing targeted minimum loss/maximum likelihood estimators: a simple illustration to build intuition Predictions from this model arebµ ∗

Reference 15

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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 2026-08-17T06:30:58.91139+00:00.

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Observation 5b027821-5786-43f4-8279-0b64beef6c67 · outbound

This paper cites Predictions from this model are bE(bµ∗|W0, A0 = 0).

Constructing targeted minimum loss/maximum likelihood estimators: a simple illustration to build intuition Predictions from this model are bE(bµ∗|W0, A0 = 0)

Reference 16

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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 2026-08-17T06:30:58.91139+00:00.

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Observation b0027aa3-4da3-4502-9067-a1e0664a5b52 · outbound

This paper cites Predictions from this model are bE ∗ (bµ∗|W0, A0 = 0).

Constructing targeted minimum loss/maximum likelihood estimators: a simple illustration to build intuition Predictions from this model are bE ∗ (bµ∗|W0, A0 = 0)

Reference 17

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verified fuzzy
raw_fallback, observed 2026-08-06T17:12:32.909317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 7f1390fe-2ed9-462d-8d05-0974f1d87a69 · outbound

This paper cites Further, as discussed in the main text, although we have shown linear targeting models to simplify notation, logistic models are recommended for better finite sample properties.

Constructing targeted minimum loss/maximum likelihood estimators: a simple illustration to build intuition Further, as discussed in the main text, although we have shown linear targeting models to simplify notation, logistic models are recommended for better finite sample properties

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:12:32.728513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Pith citing papers

No inbound Pith citation observations are available.