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Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment

As of 17 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 0 inbound Pith citation observations for arXiv:2507.17686.

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2507.17686 v3

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Outbound references

Observation c47b3d5d-1a84-4729-9d5a-2c897d26dacc · outbound

This paper cites Alternative analysis methods for time to event endpoi nts under nonproportional haz- ards: A comparative analysis,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Alternative analysis methods for time to event endpoi nts under nonproportional haz- ards: A comparative analysis,

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This paper cites The optimization was stopped, if the ℓ2-norm of the gradient gets smaller than ǫstop = 1.0 × 10−2.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment The optimization was stopped, if the ℓ2-norm of the gradient gets smaller than ǫstop = 1.0 × 10−2

Reference 2

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Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Unresolved cited work

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This paper cites Does cox analysis of a randomized survival study yield a causal treatment effect?.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Does cox analysis of a randomized survival study yield a causal treatment effect?

Reference 4

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This paper cites The hazards of per iod specific and weighted hazard ratios,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment The hazards of per iod specific and weighted hazard ratios,

Reference 5

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Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment The hazards of hazard ratios,

Reference 6

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Observation a43bda66-d3ee-4d03-922a-a0fe8f7497b5 · outbound

This paper cites Intention-to-trea t comparisons in randomized trials,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Intention-to-trea t comparisons in randomized trials,

Reference 7

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Observation 63f953dd-7544-4fe2-925d-5c1e61c765ad · outbound

This paper cites Subtleties in the inter- pretation of hazard contrasts,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Subtleties in the inter- pretation of hazard contrasts,

Reference 8

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Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Causality and the cox regression m odel,

Reference 9

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This paper cites Treatment effect quantification for tim e-to-event endpoints–estimands, analysis strategies, and beyond,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Treatment effect quantification for tim e-to-event endpoints–estimands, analysis strategies, and beyond,

Reference 10

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Observation b829c56f-36d0-4b9b-b823-16df8466de08 · outbound

This paper cites On Defense of the Hazard Ratio.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment On Defense of the Hazard Ratio

Reference 11

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Observation fe1cf4b3-de39-4b66-af50-2bc09368916c · outbound

This paper cites Causal interpretation of the ha zard ratio in ran- domized clinical trials,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Causal interpretation of the ha zard ratio in ran- domized clinical trials,

Reference 12

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This paper cites Estimating heterogeneous treatment effects with right-censored data vi a causal survival forests,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Estimating heterogeneous treatment effects with right-censored data vi a causal survival forests,

Reference 13

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Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Uses and limitations of the restricted mean survival time: Illustra tive examples from cardiovascular outcomes and mortality trials in type 2 diabetes,

Reference 14

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Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Treatment effe ct measures un- der nonproportional hazards,

Reference 15

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This paper cites Design, implem entation, and inferential issues asso- ciated with clinical trials that rely on data in electronic m edical records: a narrative review,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Design, implem entation, and inferential issues asso- ciated with clinical trials that rely on data in electronic m edical records: a narrative review,

Reference 16

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Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Estimating heterogeneous treatment effects on survi val outcomes using counterfactual censoring unbiased transformations,

Reference 17

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Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Orthogonal Survival Learners for Estimating Heterogeneous Treatment Effects from Time-to-Event Data

Reference 18

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Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Double/debiased machine learning for treat- ment and structural parameters,

Reference 19

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Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Marginal structural models to estimate the joint causal effect of nonrandomized treatmen ts,

Reference 20

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Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Unresolved cited work

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Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Unresolved cited work

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Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment An introduction to double/debiased ma chine learning,

Reference 23

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Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Full likelihood inference s in the cox model: an empirical likelihood approach,

Reference 24

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Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Marginal structuralmodels and causal inference in epidemiology,

Reference 25

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This paper cites Kernel ba yes’ rule: Bayesian inference with positive definite kernels,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Kernel ba yes’ rule: Bayesian inference with positive definite kernels,

Reference 26

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Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Applica- tion of marginal structural models in pharmacoepidemiolog ic studies: a sys- tematic review,

Reference 27

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This paper cites Functional analysis and semi-groups, 3rd printing of rev. ed. of 1957,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Functional analysis and semi-groups, 3rd printing of rev. ed. of 1957,

Reference 28

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Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment 4 (Springer, 2006)

Reference 29

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Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment History-adjusted marginal structural models and statically-optimal dynamic treatme nt regimens,

Reference 30

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Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Theory of reproducing kernels,

Reference 31

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Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Learning the kernel matrix with semidefinite progr amming,

Reference 32

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Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Fast learning rate of multiple kernel learning: Trade-off between sparsity and smoothness,

Reference 33

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Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Sparsity in mult iple kernel learning,

Reference 34

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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 bed7a136-dbc9-4a7c-972a-682880620d09 · outbound

This paper cites Consistency of the group lasso and mult iple kernel learning.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Consistency of the group lasso and mult iple kernel learning

Reference 35

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verified fuzzy
raw_fallback, observed 2026-08-15T18:25:07.363979Z

Source-reported events for the cited work

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Observation c6c92df2-31d1-4e3f-a866-62a2e6a6097c · outbound

This paper cites Hig h-dimensional additive modeling,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Hig h-dimensional additive modeling,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:25:07.320647Z

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.

source=pdf_text observed=2026-08-15T18:25:05.799259Z digest=sha256:cce301d267e0060337b5bdce58fb58571015d425ba3619ee0aaad82dc844f4a6

Observation ce44d688-8fe9-41de-b083-44249d1919e5 · outbound

This paper cites The asymptotic information in censored s urvival data,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment The asymptotic information in censored s urvival data,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:25:07.233764Z

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.

source=pdf_text observed=2026-08-15T18:25:05.824843Z digest=sha256:f524e57e460ca35d34adccf5356c466f6692b7e6a12a04c4f6d589a45f9392ce

Observation 6a900bc9-ca21-4ced-9ae3-14d0ac47368a · outbound

This paper cites Regression models and life-tables,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Regression models and life-tables,

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-15T18:25:05.812003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:25:05.812003Z digest=sha256:c9840207fc9e40f5bcec9e02f0ff9ae33d6517e8cbffac3dda8778bed7fc1c22

Observation 7e14ed55-fcc7-449c-bfb6-80501ff185d1 · outbound

This paper cites The efficiency of cox’s likelihood funct ion for censored data,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment The efficiency of cox’s likelihood funct ion for censored data,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:25:07.264004Z

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.

source=pdf_text observed=2026-08-15T18:25:05.818301Z digest=sha256:1083b7121828efcb6054247bd733d055fda6577c46fbb6deebe83be9b27c130e

Observation 8a26798f-0890-46f4-8122-8dda03b0ba41 · outbound

This paper cites Bayesian inference for cox proportional hazard models with partial likelihoods, nonl inear covariate effects and correlated observations,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Bayesian inference for cox proportional hazard models with partial likelihoods, nonl inear covariate effects and correlated observations,

Reference 40

Resolution
verified exact
doi, observed 2026-08-15T18:25:06.070241Z

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.

source=pdf_text observed=2026-08-15T18:25:05.844860Z digest=sha256:8bdb5d6f8225b22da903f487b5d674a27d6fcdb9accd3f182287e4c8b9cca3e7

Observation 7f285980-bd59-4176-914b-7256a6ff8180 · outbound

This paper cites On maximum likelihood estima tion of the semi-parametric cox model with time-varying covariates,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment On maximum likelihood estima tion of the semi-parametric cox model with time-varying covariates,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:25:07.202323Z

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.

source=pdf_text observed=2026-08-15T18:25:05.830783Z digest=sha256:edc25a1ede9477317199429e540abadbedde411dabce67f6b67de64057c5df6b

Observation e44bfdfa-5abb-4241-89e0-21a8a14e826a · outbound

This paper cites D oubly robust estimation un- der a possibly misspecified marginal structural cox model,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment D oubly robust estimation un- der a possibly misspecified marginal structural cox model,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:25:07.180274Z

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.

source=pdf_text observed=2026-08-15T18:25:05.836832Z digest=sha256:178796052701a9a26cfedcc0a4f10f60d3956eb9dcfdc81ba145496c07f4aca9

Observation bc35961f-d971-4f05-9149-ba5aa8a612b7 · outbound

This paper cites Identifiability of parameters in latent structure models with many observed variables,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Identifiability of parameters in latent structure models with many observed variables,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:25:07.121488Z

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.

source=pdf_text observed=2026-08-15T18:25:05.870100Z digest=sha256:dab37b69d5429c9ddb4b1a0285e07ff9022c2a56ac587ca88f72d45cfa3a2a87

Observation 430006a7-e4e2-4f39-9c74-2d4898143338 · outbound

This paper cites Machine learn- ing approaches to evaluate heterogeneous treatment effects i n randomized controlled trials: a 42 scoping review,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Machine learn- ing approaches to evaluate heterogeneous treatment effects i n randomized controlled trials: a 42 scoping review,

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-15T18:25:05.853490Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:25:05.853490Z digest=sha256:aca4984c57b82093868607c1b8386f3eccc97d9ed707feec14bfd18e19fc7b99

Observation 56b6e9d3-9120-4f20-838f-bd38be3f716a · outbound

This paper cites On the ma ximum penalized likelihood ap- proach for proportional hazard models with right censored s urvival data,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment On the ma ximum penalized likelihood ap- proach for proportional hazard models with right censored s urvival data,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:25:07.157582Z

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.

source=pdf_text observed=2026-08-15T18:25:05.863359Z digest=sha256:045df0bb766abd2bd4e69c446bd3bd39d5cb1dc94aa7acfd612128a08d3a113b

Observation e7dbad0b-3858-4ca8-b1b9-43462cc3dd79 · outbound

This paper cites Nonparametri c finite translation hidden markov models and extensions,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Nonparametri c finite translation hidden markov models and extensions,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:25:07.045100Z

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.

source=pdf_text observed=2026-08-15T18:25:05.886118Z digest=sha256:d0ca14a7d17ab37f9d10e08adfce527cc26c66522d3d1a20903f1fe34f410f0f

Observation 80ef1132-7f5e-400e-aeab-ca77c16a7b43 · outbound

This paper cites Parameter identifiability of discrete bayesian networks with hidden v ariables,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Parameter identifiability of discrete bayesian networks with hidden v ariables,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:25:07.094085Z

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.

source=pdf_text observed=2026-08-15T18:25:05.875239Z digest=sha256:4da87032fb451fada3b094009654f134c15f20855788f4173ef950721ebdb091

Observation 50f0e538-6e5c-4f08-a1e6-98cf5fbd55a1 · outbound

This paper cites Inference in finit e state space non parametric hidden markov models and applications,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Inference in finit e state space non parametric hidden markov models and applications,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:25:07.068220Z

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.

source=pdf_text observed=2026-08-15T18:25:05.881164Z digest=sha256:9ade77d93ed844935a960d3768a1a607469df6ca3a0646aa10608289d2e2d8e6

Observation 0a215ba4-3fff-4751-a990-4b3194357486 · outbound

This paper cites Estimating bayes fa ctors via thermodynamic integration and population mcmc,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Estimating bayes fa ctors via thermodynamic integration and population mcmc,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:25:06.970172Z

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.

source=pdf_text observed=2026-08-15T18:25:05.903675Z digest=sha256:4efc125fcccd53a49def23f9b0a552234ab5de43ecac6ace2affe9887d73f02b

Observation 223c9e4a-3964-4dea-b07f-1a4c8f1319b7 · outbound

This paper cites On structural and practical identifiability,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment On structural and practical identifiability,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:25:07.022325Z

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.

source=pdf_text observed=2026-08-15T18:25:05.891705Z digest=sha256:fdf010fea7fb74f46f5d18d8d67399ab76313d0badae3bd4f0af52cee692e5b7

Observation 9921f44c-99ff-42a2-918f-d78a05d136df · outbound

This paper cites 25 (Cambridge uni- versity press, 2009).

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment 25 (Cambridge uni- versity press, 2009)

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:25:06.995972Z

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.

source=pdf_text observed=2026-08-15T18:25:05.897460Z digest=sha256:4799013be4401b48a90fafb2188bc2584faf1cf8e61e4fc385c0bf37d1227ecd

Observation 4e48feab-bb01-4cf0-b32a-89e69128d3e6 · outbound

This paper cites an unresolved cited work.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Unresolved cited work

Reference 52

Resolution
unresolved
raw_fallback, observed 2026-08-15T18:25:06.891514Z

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.

source=pdf_text observed=2026-08-15T18:25:05.933572Z digest=sha256:296576fe9ab97f5b310d7bb279f5e696892254fd31d8d04686f320737533af4c

Observation 17533aaa-4f80-4f67-a633-88efb3d0ecf5 · outbound

This paper cites A widely applicable bayesian informa tion criterion,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment A widely applicable bayesian informa tion criterion,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:25:06.944980Z

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.

source=pdf_text observed=2026-08-15T18:25:05.911640Z digest=sha256:fa8522b7647856f217113cc1f0cbb24ecc2e13b4cc010eff7206f3a6a9b07067

Observation 504730ca-e023-4e02-86bb-3d75162d13f4 · outbound

This paper cites A bayesian informat ion criterion for singular models,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment A bayesian informat ion criterion for singular models,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:25:06.921324Z

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.

source=pdf_text observed=2026-08-15T18:25:05.917592Z digest=sha256:0fd2167d9c8b84cf0fc1f6c27a74dbf21d46dda4094629844d4e061fd4eb0228

Observation 9500e47b-29b1-4727-82ab-b23f7b22f3b5 · outbound

This paper cites Kernel independent compone nt analysis,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Kernel independent compone nt analysis,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:25:06.846724Z

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.

source=pdf_text observed=2026-08-15T18:25:05.953267Z digest=sha256:3236c549a9868ef622ebed00a8272e78eec725acc8665ef9640944dc57198af3

Observation 063d1fc9-2406-46d3-b5e4-ce59c7b5452a · outbound

This paper cites , An introduction to sequential Monte Carlo , Vol.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment , An introduction to sequential Monte Carlo , Vol

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:25:06.871218Z

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.

source=pdf_text observed=2026-08-15T18:25:05.940857Z digest=sha256:9243f120dca5c464608a797904b0e28ff1f0870dab5bfcd6df70722d5fbe3bec

Observation 1a311843-46c3-4ba2-a470-62abc10c8fb6 · outbound

This paper cites Probability asymptotics: notes on notation.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Probability asymptotics: notes on notation

Reference 57

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unresolved
no resolver link, observed 2026-08-15T18:25:05.946906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:25:05.946906Z digest=sha256:5de21747878e841439ecd8f3a26eb7d0bc42ad72286558d18ca654b9a6e5ebbf

Observation 9e2cef12-c88a-4c02-b7dc-d56705f03c67 · outbound

This paper cites S tatistical consistency of kernel canonical correlation analysis,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment S tatistical consistency of kernel canonical correlation analysis,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:25:06.785402Z

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.

source=pdf_text observed=2026-08-15T18:25:05.972622Z digest=sha256:91f42094dbaa0a8ced97150b5dfd38d8ddf0d73ba3060dd54c4b3e2e176de997

Observation 4170d6b2-5083-409e-bb8c-71e0b8345a82 · outbound

This paper cites an unresolved cited work.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Unresolved cited work

Reference 59

Resolution
unresolved
raw_fallback, observed 2026-08-15T18:25:07.817532Z

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.

source=pdf_text observed=2026-08-15T18:25:05.571893Z digest=sha256:93dffa56e0bf19e06de8c4fb046f08ca8ece3c47d28f8bd6038a7cefc3571947

Observation 0924b9bf-8b65-464f-8e87-3bbaac4d4e1c · outbound

This paper cites On the limited memory bfgs method for large scale opti- mization,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment On the limited memory bfgs method for large scale opti- mization,

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:25:06.825793Z

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.

source=pdf_text observed=2026-08-15T18:25:05.959078Z digest=sha256:b27f8525889ee22efcf93b7974fe691880f9f58ee46bd1b980527f791ee8c16e

Observation 5c693531-4b4f-4180-9dc3-dcb6891aaf3a · outbound

This paper cites 2 (MIT press Cambridge, MA, 2006).

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment 2 (MIT press Cambridge, MA, 2006)

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:25:06.806157Z

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.

source=pdf_text observed=2026-08-15T18:25:05.964843Z digest=sha256:cadf7beb9b5a247040a758c3a5ec6217c780d3fa50919413246a0810b80bcd79

Observation 722e46da-2210-404d-92a9-4dd4d691ee39 · outbound

This paper cites Theoretical analysis of density ratio estimation,.

Debiased maximum-likelihood estimators for hazard ratios under kernel-based machine-learning adjustment Theoretical analysis of density ratio estimation,

Reference 62

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verified fuzzy
raw_fallback, observed 2026-08-15T18:25:06.760757Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T18:25:05.980549Z digest=sha256:a116b88ba0265902d64a158b1109c3cf0086982b19786c80c177ee557a140dd8

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