Achievable distributional robustness when the robust risk is only partially identified | Paper Citation Record

Observation c7e7e3f7-34ab-4db2-9da0-d2ea08bd3aa3 · outbound

This paper cites Robust solutions of optimization problems affected by uncertain probabilities.

Achievable distributional robustness when the robust risk is only partially identified Robust solutions of optimization problems affected by uncertain probabilities

Reference 1

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Observation 5d921cc1-dd23-4e27-a6cb-82db5c495633 · outbound

This paper cites Learning models with uniform performance via distributionally robust optimization.

Achievable distributional robustness when the robust risk is only partially identified Learning models with uniform performance via distributionally robust optimization

Reference 2

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Observation 241eeec4-76ef-4921-9700-d6bdd1351664 · outbound

This paper cites Goodfellow, Jonathon Shlens, and Christian Szegedy.

Achievable distributional robustness when the robust risk is only partially identified Goodfellow, Jonathon Shlens, and Christian Szegedy

Reference 3

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Observation f19ce83e-4b7c-4d72-93e4-cbde53aa4c36 · outbound

This paper cites Towards deep learning models resistant to adversarial attacks.

Achievable distributional robustness when the robust risk is only partially identified Towards deep learning models resistant to adversarial attacks

Reference 4

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This paper cites Domain adaptation with multiple sources.

Achievable distributional robustness when the robust risk is only partially identified Domain adaptation with multiple sources

Reference 5

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Observation f2f229e0-0e1f-4129-901a-c8998f1ce454 · outbound

This paper cites Maximin effects in inhomogeneous large-scale data.

Achievable distributional robustness when the robust risk is only partially identified Maximin effects in inhomogeneous large-scale data

Reference 6

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This paper cites Hashimoto, and Percy Liang.

Achievable distributional robustness when the robust risk is only partially identified Hashimoto, and Percy Liang

Reference 7

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Observation 7356d6ce-175d-493d-9c6b-2feb21ed5cc6 · outbound

This paper cites Invariance, causality and robustness.

Achievable distributional robustness when the robust risk is only partially identified Invariance, causality and robustness

Reference 8

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Observation 0f4faa8b-be3b-4529-b515-8c2dfa530ea5 · outbound

This paper cites Causality from a distributional robustness point of view.

Achievable distributional robustness when the robust risk is only partially identified Causality from a distributional robustness point of view

Reference 9

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Observation d3b31aea-435b-4eb2-9d71-1900f93ccaf9 · outbound

This paper cites Causality-oriented robustness: exploiting general noise interventions.

Achievable distributional robustness when the robust risk is only partially identified Causality-oriented robustness: exploiting general noise interventions

Reference 10

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Observation a9bcb5ce-e106-40d0-867f-b51be31436a1 · outbound

This paper cites Adversarial training and robustness for multiple perturbations.

Achievable distributional robustness when the robust risk is only partially identified Adversarial training and robustness for multiple perturbations

Reference 11

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Observation 4c3fd8d2-c6f5-449b-b8a8-453e5c0c5151 · outbound

This paper cites Transfer of Adversarial Robustness Between Perturbation Types.

Achievable distributional robustness when the robust risk is only partially identified Transfer of Adversarial Robustness Between Perturbation Types

Reference 12

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Observation 3e0a68a5-a50e-4992-a1b6-6a5525f9613c · outbound

This paper cites Causal inference by using invariant prediction: identifica- tion and confidence intervals.

Achievable distributional robustness when the robust risk is only partially identified Causal inference by using invariant prediction: identifica- tion and confidence intervals

Reference 13

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Observation 54983709-4e7f-414c-bdfc-a38e57ff767a · outbound

This paper cites Invariant models for causal transfer learning.

Achievable distributional robustness when the robust risk is only partially identified Invariant models for causal transfer learning

Reference 14

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Observation 1ec4d62e-5c92-4e82-9be0-7e3962b918d0 · outbound

This paper cites Invariant Risk Minimization.

Achievable distributional robustness when the robust risk is only partially identified Invariant Risk Minimization

Reference 15

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Observation a51a8a4d-bc04-42f3-8966-b9f659ae485e · outbound

This paper cites Out-of-distribution generalization via risk extrapolation (REx).

Achievable distributional robustness when the robust risk is only partially identified Out-of-distribution generalization via risk extrapolation (REx)

Reference 16

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Observation aecc1cbc-de81-4616-9f9c-b6fc96a78fb1 · outbound

This paper cites Varshney.

Achievable distributional robustness when the robust risk is only partially identified Varshney

Reference 17

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Observation 7eb9b07e-a0d7-4e66-b001-6ff8ddcd8341 · outbound

This paper cites Invariant risk minimization games.

Achievable distributional robustness when the robust risk is only partially identified Invariant risk minimization games

Reference 18

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Observation f8fe05dd-3b15-4032-baa3-ffed2a4ea45d · outbound

This paper cites Does invariant risk minimization capture invariance? In International Conference on Artificial Intelligence and Statistics , pages 4069–4077.

Achievable distributional robustness when the robust risk is only partially identified Does invariant risk minimization capture invariance? In International Conference on Artificial Intelligence and Statistics , pages 4069–4077

Reference 19

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Observation e744f5be-6d12-46c6-b3d2-c46435004275 · outbound

This paper cites The risks of invariant risk minimization.

Achievable distributional robustness when the robust risk is only partially identified The risks of invariant risk minimization

Reference 20

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Observation 09b33919-37d6-45a7-b86f-3fdd37b1ef4f · outbound

This paper cites Anchor regression: Heterogeneous data meet causality.

Achievable distributional robustness when the robust risk is only partially identified Anchor regression: Heterogeneous data meet causality

Reference 21

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Observation f15f46f8-b9f4-4a77-8521-ee85df8b55e8 · outbound

This paper cites Partial identification in econometrics.

Achievable distributional robustness when the robust risk is only partially identified Partial identification in econometrics

Reference 22

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Observation be1ec8c3-4de8-4d62-a558-4ed30fdd0262 · outbound

This paper cites From perfect to practical: Partial identification methods for causal inference in strategic management research.

Achievable distributional robustness when the robust risk is only partially identified From perfect to practical: Partial identification methods for causal inference in strategic management research

Reference 23

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Observation e71b23fb-b668-49e1-81e7-c8aaec7e5333 · outbound

This paper cites Assouad, Fano, and le Cam.

Achievable distributional robustness when the robust risk is only partially identified Assouad, Fano, and le Cam

Reference 24

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Observation f9734c66-5b32-4aa3-ae26-ec0cfee41d10 · outbound

This paper cites Exploiting independent instruments: Identification and distribution generalization.

Achievable distributional robustness when the robust risk is only partially identified Exploiting independent instruments: Identification and distribution generalization

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:28:00.874823Z

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Observation bd00fb44-6da8-42b2-a582-7f426c8df798 · outbound

This paper cites Partial transportability for domain generalization.

Achievable distributional robustness when the robust risk is only partially identified Partial transportability for domain generalization

Reference 26

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Observation 17b7fcd8-56cc-4b2f-be2a-b33eff3e9e76 · outbound

This paper cites Improving predictive inference under covariate shift by weighting the log-likelihood function.

Achievable distributional robustness when the robust risk is only partially identified Improving predictive inference under covariate shift by weighting the log-likelihood function

Reference 27

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Observation e9f0b9c6-7c21-4c6a-bc4c-49778ee28d87 · outbound

This paper cites Identification, pages 65–77.

Achievable distributional robustness when the robust risk is only partially identified Identification, pages 65–77

Reference 28

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Observation 52fed9f3-3049-4ef4-83bb-6297c2b26179 · outbound

This paper cites Advanced Econometrics.

Achievable distributional robustness when the robust risk is only partially identified Advanced Econometrics

Reference 29

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This paper cites Instrumental variables.

Achievable distributional robustness when the robust risk is only partially identified Instrumental variables

Reference 30

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Observation 8058e1ff-4f84-46c2-9695-b75c0e2b53cc · outbound

This paper cites Domain adaptation under structural causal models.

Achievable distributional robustness when the robust risk is only partially identified Domain adaptation under structural causal models

Reference 31

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Observation 690f4bed-9846-4398-aff6-fc5c2e7502de · outbound

This paper cites Mapping information-rich genotype- phenotype landscapes with genome-scale Perturb-seq.

Achievable distributional robustness when the robust risk is only partially identified Mapping information-rich genotype- phenotype landscapes with genome-scale Perturb-seq

Reference 32

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Observation bb4bf0bf-f7b7-451c-a120-72a77ffff7f6 · outbound

This paper cites Assessing the overall and partial causal well-specification of nonlinear additive noise models.

Achievable distributional robustness when the robust risk is only partially identified Assessing the overall and partial causal well-specification of nonlinear additive noise models

Reference 33

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Observation a9c8d050-e407-4ca2-9863-fa5148d506db · outbound

This paper cites Evaluating robustness to dataset shift via parametric robustness sets.

Achievable distributional robustness when the robust risk is only partially identified Evaluating robustness to dataset shift via parametric robustness sets

Reference 34

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Observation d34e5991-2abf-4e85-88b1-90bf2ef32967 · outbound

This paper cites Learning linear causal representations from interventions under general nonlinear mixing.

Achievable distributional robustness when the robust risk is only partially identified Learning linear causal representations from interventions under general nonlinear mixing

Reference 35

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Observation a0eed730-7eb6-4b6a-bdd5-ec4d32714aa9 · outbound

This paper cites Active learning for optimal intervention design in causal models.

Achievable distributional robustness when the robust risk is only partially identified Active learning for optimal intervention design in causal models

Reference 36

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Observation bec5a443-0ed2-401d-8786-1942e11819df · outbound

This paper cites Active invariant causal prediction: Experiment selection through stability.

Achievable distributional robustness when the robust risk is only partially identified Active invariant causal prediction: Experiment selection through stability

Reference 37

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Observation f9ab65c3-c550-4faf-a5a1-2e5c64952d62 · outbound

This paper cites Certifiable distributional robustness with principled adversarial training.

Achievable distributional robustness when the robust risk is only partially identified Certifiable distributional robustness with principled adversarial training

Reference 38

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Observation 6396bb20-4346-4aab-ac50-ba189feb6025 · outbound

This paper cites Data-driven distributionally robust optimization using the Wasser- stein metric: Performance guarantees and tractable reformulations.

Achievable distributional robustness when the robust risk is only partially identified Data-driven distributionally robust optimization using the Wasser- stein metric: Performance guarantees and tractable reformulations

Reference 39

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Observation 47a0866e-5b17-44af-9e21-3805fc70365f · outbound

This paper cites Environment Invariant Linear Least Squares.

Achievable distributional robustness when the robust risk is only partially identified Environment Invariant Linear Least Squares

Reference 40

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Observation c94ac935-ee59-4923-a99a-32f099007b4f · outbound

This paper cites Domain adaptation by using causal inference to predict invariant conditional distributions.

Achievable distributional robustness when the robust risk is only partially identified Domain adaptation by using causal inference to predict invariant conditional distributions

Reference 41

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Observation dccca8aa-fea6-49c4-9b31-546c517d7d6e · outbound

This paper cites Gradient matching for domain generalization.

Achievable distributional robustness when the robust risk is only partially identified Gradient matching for domain generalization

Reference 42

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Observation 96c43e30-67da-4446-a8c2-4a89d5eaa7e2 · outbound

This paper cites Risk Variance Penalization.

Achievable distributional robustness when the robust risk is only partially identified Risk Variance Penalization

Reference 43

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Observation c1b1a6d4-c53b-4948-89a5-80954f900ca0 · outbound

This paper cites Invariance principle meets information bottleneck for out-of-distribution generalization.

Achievable distributional robustness when the robust risk is only partially identified Invariance principle meets information bottleneck for out-of-distribution generalization

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:28:00.639892Z

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Observation 73c469a8-acf1-43d8-aef1-774e30002679 · outbound

This paper cites Distributional robustness of K-class estimators and the PULSE.

Achievable distributional robustness when the robust risk is only partially identified Distributional robustness of K-class estimators and the PULSE

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:28:00.625350Z

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Observation daa45feb-6f7f-4129-80bf-4a9131e9d5d6 · outbound

This paper cites A causal framework for distribution generalization.

Achievable distributional robustness when the robust risk is only partially identified A causal framework for distribution generalization

Reference 46

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Observation a6f6ce40-cd28-402d-ab18-34a18db7bad9 · outbound

This paper cites Distributional anchor regression.

Achievable distributional robustness when the robust risk is only partially identified Distributional anchor regression

Reference 47

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Observation 6d6847d3-3077-4ed0-9f38-5eb18f0b495e · outbound

This paper cites Incorporating unlabeled data into distribu- tionally robust learning.

Achievable distributional robustness when the robust risk is only partially identified Incorporating unlabeled data into distribu- tionally robust learning

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:28:00.583508Z

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Observation e44fbf87-15c1-40d4-9c64-51ed610c7ba1 · outbound

This paper cites Distributionally robust optimization with data geometry.

Achievable distributional robustness when the robust risk is only partially identified Distributionally robust optimization with data geometry

Reference 49

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Observation 7dd81f81-c726-4b6c-92f2-71aa5a9f19af · outbound

This paper cites Causality: Models, Reasoning and Inference.

Achievable distributional robustness when the robust risk is only partially identified Causality: Models, Reasoning and Inference

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:28:00.555415Z

Source-reported events for the cited work

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Observation 46923df1-4106-44be-bcf6-a9627f8d6af0 · outbound

This paper cites Identification of causal effects using instrumental variables.

Achievable distributional robustness when the robust risk is only partially identified Identification of causal effects using instrumental variables

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:28:00.539491Z

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Observation a596e246-a950-499b-a8bf-ea6fc8d636c2 · outbound

This paper cites Deep IV: A flexible approach for counterfactual prediction.

Achievable distributional robustness when the robust risk is only partially identified Deep IV: A flexible approach for counterfactual prediction

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:28:00.525332Z

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Observation cf3f3764-da05-4bea-95e0-80d17db65ad5 · outbound

This paper cites Kernel instrumental variable regression.

Achievable distributional robustness when the robust risk is only partially identified Kernel instrumental variable regression

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:28:00.510965Z

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Observation cc662b8b-ec2d-43aa-a04c-6cb242f7bd72 · outbound

This paper cites Deep generalized method of moments for instrumental variable analysis.

Achievable distributional robustness when the robust risk is only partially identified Deep generalized method of moments for instrumental variable analysis

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:28:00.496831Z

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Observation 727f3c93-7314-462a-81a5-33239241415a · outbound

This paper cites Dual instrumental variable regression.

Achievable distributional robustness when the robust risk is only partially identified Dual instrumental variable regression

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:28:00.481721Z

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Observation 798666b2-a7f1-4998-8f4f-12832499a8cf · outbound

This paper cites In search of lost domain generalization.

Achievable distributional robustness when the robust risk is only partially identified In search of lost domain generalization

Reference 56

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Observation da938680-17f1-4bbb-a093-bb14b8114b25 · outbound

This paper cites Elements of causal inference: foundations and learning algorithms.

Achievable distributional robustness when the robust risk is only partially identified Elements of causal inference: foundations and learning algorithms

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:28:00.458342Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6554645c-f67c-47da-8e52-ca20bab9a566 · outbound

This paper cites A useful variant of the Davis–Kahan theorem for statisticians.

Achievable distributional robustness when the robust risk is only partially identified A useful variant of the Davis–Kahan theorem for statisticians

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:28:00.443558Z

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Observation c43ca387-a64e-4194-b4cc-76577ea35ff1 · outbound

This paper cites Asymptotic statistics, volume 3.

Achievable distributional robustness when the robust risk is only partially identified Asymptotic statistics, volume 3

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-09T11:28:00.223501Z

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Observation 028352cd-62a5-468d-96ee-40007211cd0d · outbound

This paper cites CausalBench: A Large-scale Benchmark for Network Inference from Single-cell Perturbation Data.

Achievable distributional robustness when the robust risk is only partially identified CausalBench: A Large-scale Benchmark for Network Inference from Single-cell Perturbation Data

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-09T11:28:00.227954Z

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Observation b7337d9c-1838-4f44-9673-de1fda660f7d · outbound

This paper cites Repurposing CRISPR as an RNA-guided platform for sequence-specific control of gene expression.

Achievable distributional robustness when the robust risk is only partially identified Repurposing CRISPR as an RNA-guided platform for sequence-specific control of gene expression

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:28:00.420152Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2fac6df4-d4a4-4066-8572-c653f50d3f84 · outbound

This paper cites dominated reference environment.

Achievable distributional robustness when the robust risk is only partially identified dominated reference environment

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:28:00.404685Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 898cc886-2728-484a-a7fb-5a6613abf329 · outbound

This paper cites Under the assumption of the consistency of the nuisance parameter estimators, we can now show that (21) is a consistent estimator of the worst-case robust predictor.

Achievable distributional robustness when the robust risk is only partially identified Under the assumption of the consistency of the nuisance parameter estimators, we can now show that (21) is a consistent estimator of the worst-case robust predictor

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:28:00.389948Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c19fedd5-b130-408c-b2da-517dcb726bd5 · outbound

This paper cites initial guess.

Achievable distributional robustness when the robust risk is only partially identified initial guess

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:28:00.373575Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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