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Paper Citation Record · LEDGER

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds

As of 14 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:2607.23448.

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

pith.paper-citation-record.v1
2607.23448 v1

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-30T21:57:09.816674Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

48 of 48 outbound references displayed

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  • unresolved48
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a07e0911-a147-4a09-a318-e5d77b1b07c9 · outbound

This paper cites Communication, Simulation, and Intelligent Agents: Implications of Personal Intelligent Machines for Medical Education.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Communication, Simulation, and Intelligent Agents: Implications of Personal Intelligent Machines for Medical Education

Reference 1

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Observation 614ef0a3-ec9f-4b80-9e01-b5636c9bed4c · outbound

This paper cites Classification Problem Solving.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Classification Problem Solving

Reference 2

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source=arxiv_source observed=2026-07-30T21:57:09.582852Z digest=sha256:3e1e8f5c6c7c64d85165815ea25943d5c48768193e8390a13b5fc7fb80416eeb

Observation 23ad29c5-540b-446a-acd7-237e33d2f765 · outbound

This paper cites , title =.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds , title =

Reference 3

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source=arxiv_source observed=2026-07-30T21:57:09.589735Z digest=sha256:0cf640151a81271602c7568087808c950b71e096a9151df1d8f93594caceacea

Observation 348e7ce2-70d6-480d-a446-82b2a620bc1e · outbound

This paper cites New Ways to Make Microcircuits Smaller---Duplicate Entry.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds New Ways to Make Microcircuits Smaller---Duplicate Entry

Reference 4

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Observation 928d9beb-4311-43aa-89a3-fae35b89e8b1 · outbound

This paper cites Clancey and Glenn Rennels , abstract =.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Clancey and Glenn Rennels , abstract =

Reference 5

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source=arxiv_source observed=2026-07-30T21:57:09.600364Z digest=sha256:22268189f900e0fe3d97ea711063b4dfbacd78e31950bd3d1283bb22be4bd948

Observation 60decd1a-a19c-4ebe-b4d7-57d5d4d4c8c9 · outbound

This paper cites and Rennels, Glenn R.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds and Rennels, Glenn R

Reference 6

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Observation c6a8b80a-0d0c-4379-af11-cd2c3c1a53ca · outbound

This paper cites Poligon: A System for Parallel Problem Solving.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Poligon: A System for Parallel Problem Solving

Reference 7

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source=arxiv_source observed=2026-07-30T21:57:09.611151Z digest=sha256:caa37f9c2a67a3dc91f1ac1387398790392a83a4496802ff22ab1793c2aed6c0

Observation f6e5fa67-7079-409a-9fb1-f9a2338fede6 · outbound

This paper cites Transfer of Rule-Based Expertise through a Tutorial Dialogue.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Transfer of Rule-Based Expertise through a Tutorial Dialogue

Reference 8

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source=arxiv_source observed=2026-07-30T21:57:09.615907Z digest=sha256:5b648babffb87142eb886b0ae98612d11ce70de07eef8cb065bc991631bc7a24

Observation 0c26eb3e-abd8-415b-9e25-c80c8ac14449 · outbound

This paper cites The Engineering of Qualitative Models.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds The Engineering of Qualitative Models

Reference 9

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Observation 34ab0130-516e-4b46-969c-f603d8f13111 · outbound

This paper cites 2017 , eprint=.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds 2017 , eprint=

Reference 10

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Observation c0e05073-c986-412e-bbe5-6733ffee08a2 · outbound

This paper cites Pluto: The 'Other' Red Planet.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Pluto: The 'Other' Red Planet

Reference 11

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Observation 5d27264c-347a-46c3-8faf-7bf2da6e770d · outbound

This paper cites and de Freitas, Nando , journal=.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds and de Freitas, Nando , journal=

Reference 12

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Observation 0b679054-809d-4f59-8438-801aff975426 · outbound

This paper cites International conference on artificial intelligence and statistics , pages=.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds International conference on artificial intelligence and statistics , pages=

Reference 13

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Observation 36628711-3663-4b0e-92e3-7d10f4557327 · outbound

This paper cites Recent advances in optimization and modeling of contemporary problems , pages=.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Recent advances in optimization and modeling of contemporary problems , pages=

Reference 14

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Observation 81e4fd2a-6eea-452f-b7d8-2cac3ad849c7 · outbound

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Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds , author=

Reference 15

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Observation e3bf2587-8874-41f1-a874-d009d9da3d2e · outbound

This paper cites Bayesian Analysis , number =.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Bayesian Analysis , number =

Reference 16

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Observation 8facfe6b-ddcf-45af-9d9b-cabd1d52497f · outbound

This paper cites Advances in neural information processing systems , volume=.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Advances in neural information processing systems , volume=

Reference 17

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Observation 4bb05a07-0d75-4d4b-a739-6ba23c964627 · outbound

This paper cites Advances in neural information processing systems , volume=.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Advances in neural information processing systems , volume=

Reference 18

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Observation bf1b913f-9c0f-4417-a22e-8836ef631439 · outbound

This paper cites Advances in neural information processing systems , volume=.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Advances in neural information processing systems , volume=

Reference 19

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Observation 4f91fcf0-cfc9-4547-b9ef-45413ab5f8a5 · outbound

This paper cites Learning based convex approximation for constrained parametric optimization.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Learning based convex approximation for constrained parametric optimization

Reference 20

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Observation b92c0615-f6cc-43d7-9154-c4b012f3e328 · outbound

This paper cites arXiv preprint arXiv:2512.20270 , year=.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds arXiv preprint arXiv:2512.20270 , year=

Reference 21

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Observation ac9a6269-672d-4fe4-9cdc-ac0fabf69689 · outbound

This paper cites IEEE Communications Letters , volume=.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds IEEE Communications Letters , volume=

Reference 22

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Observation 81d9bf38-4afc-4f57-99cf-687b5251709f · outbound

This paper cites A Distributed Surrogate-Assisted Evolutionary Algorithm for Heterogeneously Expensive Constrained Optimization , year=.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds A Distributed Surrogate-Assisted Evolutionary Algorithm for Heterogeneously Expensive Constrained Optimization , year=

Reference 23

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Observation 5cc86d8e-c269-4f54-899f-33aabea46251 · outbound

This paper cites A Surrogate-Assisted Evolutionary Framework With Regions of Interests-Based Data Selection for Expensive Constrained Optimization , year=.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds A Surrogate-Assisted Evolutionary Framework With Regions of Interests-Based Data Selection for Expensive Constrained Optimization , year=

Reference 24

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Observation 0d96267b-b0bc-4478-b471-69ec9361b478 · outbound

This paper cites Constrained Bayesian Optimization: A Review , year=.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Constrained Bayesian Optimization: A Review , year=

Reference 25

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Observation 6e236483-e480-4448-850d-6db90c325a9e · outbound

This paper cites Bayesian Optimization with Unknown Constraints.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Bayesian Optimization with Unknown Constraints

Reference 26

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Observation b4b79ca1-6e9d-4c4b-960d-55f13c81ae6f · outbound

This paper cites The computer journal , volume=.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds The computer journal , volume=

Reference 27

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Observation 67a286d4-8db1-429f-8e9b-cd81ef2e744b · outbound

This paper cites Advances in neural information processing systems , volume=.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Advances in neural information processing systems , volume=

Reference 28

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Observation 5f72db85-6c44-42cf-9019-52b13505cd06 · outbound

This paper cites Biometrika , volume=.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Biometrika , volume=

Reference 29

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Observation 19088172-2508-4903-b7a5-5e11306ad576 · outbound

This paper cites Advances in neural information processing systems , volume=.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Advances in neural information processing systems , volume=

Reference 30

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source=arxiv_source observed=2026-07-30T21:57:09.728487Z digest=sha256:7a28e050fcae667e6a646759c4bb7abfdf82451fd433cc29240c6f0c1f1f3900

Observation cfc23e08-9b9b-4d48-bb18-70cfe46ea704 · outbound

This paper cites Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 31

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Observation 30ac0585-346a-4eaf-962d-ea7806c1c5c4 · outbound

This paper cites Learning to Guide Random Search.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Learning to Guide Random Search

Reference 32

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Observation 9e53b915-a178-468b-97a2-4d80c58bbf0c · outbound

This paper cites Proceedings of the IEEE conference on computer vision and pattern recognition , pages=.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Proceedings of the IEEE conference on computer vision and pattern recognition , pages=

Reference 33

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Observation b1bcc8ac-d3e8-4946-99af-5ef072cad3f0 · outbound

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Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Technometrics , volume=

Reference 34

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Observation fddcbe6b-e000-4bbe-8faf-67c54ee5e8fe · outbound

This paper cites Towards a new evolutionary computation: Advances in the estimation of distribution algorithms , pages=.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Towards a new evolutionary computation: Advances in the estimation of distribution algorithms , pages=

Reference 35

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source=arxiv_source observed=2026-07-30T21:57:09.753850Z digest=sha256:ab5b22d8c4c8c9809f9317fa89299ab7b161a6df67464e507aad4a55b3159037

Observation d6415763-5c0c-44e6-a014-92703040b1d2 · outbound

This paper cites Proceedings of the 14th annual conference on Genetic and evolutionary computation , pages=.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Proceedings of the 14th annual conference on Genetic and evolutionary computation , pages=

Reference 36

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Observation 5bd0aed0-cf54-4fa8-97cc-175838a90365 · outbound

This paper cites Journal of Applied Mechanics , volume=.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Journal of Applied Mechanics , volume=

Reference 37

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Observation bcbb507c-f9f6-4fbd-abef-13ee03fc7adb · outbound

This paper cites Nanyang Technological University, Singapore , volume=.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Nanyang Technological University, Singapore , volume=

Reference 38

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source=arxiv_source observed=2026-07-30T21:57:09.768309Z digest=sha256:71bc732706b9c98ff2df82e81a06facc51ce0b353b3622d83d0bc1604063b5fd

Observation fd0f99fe-dabb-4b5f-8fdd-f1126e172bed · outbound

This paper cites Yu et al.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Yu et al

Reference 39

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-30T21:57:09.773048Z digest=sha256:8290dfe0086c72a9fba1f349ee70156767fceff2e4610279a861c73194027df6

Observation b9b68e85-5586-4c5c-94ee-b5216e6579ae · outbound

This paper cites Proceedings of the conference on adaptive computing in engineering design and control , volume=.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Proceedings of the conference on adaptive computing in engineering design and control , volume=

Reference 40

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no resolver link, observed 2026-07-30T21:57:09.778057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-30T21:57:09.778057Z digest=sha256:c652adce6b0cf66a52daa44e9d1be805fa7e652fd0e99bd6ec3dbd7e5c6e12f7

Observation fd95abcc-bb09-43a2-ae11-48332484e52b · outbound

This paper cites Computers & Structures , volume=.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Computers & Structures , volume=

Reference 41

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unresolved
no resolver link, observed 2026-07-30T21:57:09.782934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-30T21:57:09.782934Z digest=sha256:a062d3a0320b503e25628e0e027d0089b2ef64e864bb61cc65bcb663939c2fcc

Observation 223e1402-0de7-4fba-9333-595b0bba328f · outbound

This paper cites Engineering computations , volume=.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Engineering computations , volume=

Reference 42

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no resolver link, observed 2026-07-30T21:57:09.787727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-30T21:57:09.787727Z digest=sha256:a756615ec5e8c08b44cb9b598b22195c0fe9b66f90d8cc525766d9c879718833

Observation c267ff01-3ffa-4cef-bb00-16e519b346be · outbound

This paper cites Journal of Mechanical Design , volume=.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Journal of Mechanical Design , volume=

Reference 43

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unresolved
no resolver link, observed 2026-07-30T21:57:09.792764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-30T21:57:09.792764Z digest=sha256:6534aa8fafec6e7b77f9734aed10faafc5d3f7ad3dd265a273f85db7100b8ced

Observation 5e590b0a-fe70-4eca-92a5-5cd015bab552 · outbound

This paper cites International journal of vehicle design , volume=.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds International journal of vehicle design , volume=

Reference 44

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no resolver link, observed 2026-07-30T21:57:09.797361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-30T21:57:09.797361Z digest=sha256:24dbc4d73c71d79fdeaa60391496238a73357aa5fa3267f6ac9255ba31027e05

Observation d32ae1a5-ba3b-4a3b-aad6-0666e92a9abf · outbound

This paper cites Advances in neural information processing systems , volume=.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Advances in neural information processing systems , volume=

Reference 45

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no resolver link, observed 2026-07-30T21:57:09.802542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-30T21:57:09.802542Z digest=sha256:0d3ff7321880f75a711320ecf3641ef726b43118358104be683e07b063be9d14

Observation 3c3dd18d-c6ea-4831-8049-783ceab67db6 · outbound

This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , volume=.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Proceedings of the AAAI Conference on Artificial Intelligence , volume=

Reference 46

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no resolver link, observed 2026-07-30T21:57:09.807420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-30T21:57:09.807420Z digest=sha256:945d8296d4bed2757ee5e4c6e79e9c34d03d00ee1f76b3c0060ba3439902609e

Observation 15e24d04-76b6-400f-9495-17029f101c3e · outbound

This paper cites IEEE Transactions on Evolutionary Computation , year=.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds IEEE Transactions on Evolutionary Computation , year=

Reference 47

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no resolver link, observed 2026-07-30T21:57:09.812141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-30T21:57:09.812141Z digest=sha256:fbb4fc38cf2b0ca8eb4bc793c38913506244964a3027a920a30f212b15129c88

Observation a2534b5d-bb09-4dee-88b3-a82becf063fa · outbound

This paper cites Pareto Set Learning for Neural Multi-objective Combinatorial Optimization.

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds Pareto Set Learning for Neural Multi-objective Combinatorial Optimization

Reference 48

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no resolver link, observed 2026-07-30T21:57:09.816674Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-30T21:57:09.816674Z digest=sha256:6caea884b9c0984ba5328dada85753db9ab91afc097ba84a042b99aef334d7a5

Pith citing papers

No inbound Pith citation observations are available.