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Paper Citation Record · LEDGER

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs

As of 9 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2608.03026.

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

pith.paper-citation-record.v1
2608.03026 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T04:20:56.532751Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

40 of 40 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6a1434ef-b1cc-4eff-8cc3-a1f156571fa8 · outbound

This paper cites AI-native O-RA N archi- tectures for 6G: Toward real-time adaptation, conflict reso lution, and efficient resource management,.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs AI-native O-RA N archi- tectures for 6G: Toward real-time adaptation, conflict reso lution, and efficient resource management,

Reference 1

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Observation 31576617-b875-444a-ba66-08c3e2692311 · outbound

This paper cites A Systematic Perspective on Co mmuni- cation Innovations Toward 6G,.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs A Systematic Perspective on Co mmuni- cation Innovations Toward 6G,

Reference 2

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Observation 7e4cfaef-3698-4917-ac61-8e7b5bf6801b · outbound

This paper cites Joint sensing, communication, and computation for vertical fede rated edge learning in edge perception networks,.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Joint sensing, communication, and computation for vertical fede rated edge learning in edge perception networks,

Reference 3

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Observation d52af9e1-d318-488f-af46-9b2d88b01cfa · outbound

This paper cites Vision-language mo dels for vision tasks: A survey,.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Vision-language mo dels for vision tasks: A survey,

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 7dd25989-bf2d-445c-93e9-4ba262cd8fa6 · outbound

This paper cites Lambo: Large AI model empowered edge intelligence,.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Lambo: Large AI model empowered edge intelligence,

Reference 5

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Observation f1e771b8-11fc-4dfa-a525-16eb4c66bf16 · outbound

This paper cites Sense Smarter, Think Better: A Survey on Edge Perception for Next-Generation Networks.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Sense Smarter, Think Better: A Survey on Edge Perception for Next-Generation Networks

Reference 6

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Observation eed8dff9-76db-488a-9640-b2cda83db008 · outbound

This paper cites Key Challenges and Research Directions for Space-Air-Ground Integrated Emergency Com munication Networks,.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Key Challenges and Research Directions for Space-Air-Ground Integrated Emergency Com munication Networks,

Reference 7

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 8c1fd16a-35aa-46b0-a172-1f2c235310dc · outbound

This paper cites Mobil e edge intelligence for large language models: A contemporary sur vey,.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Mobil e edge intelligence for large language models: A contemporary sur vey,

Reference 8

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Observation c4876f69-b46a-465c-b4a8-a08f4c954c7b · outbound

This paper cites Closing the generalization gap in parameter-efficient federated ed ge learning,.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Closing the generalization gap in parameter-efficient federated ed ge learning,

Reference 9

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Observation 9958562c-9ceb-4bb2-aae8-1e37696e4a60 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Gemini: A Family of Highly Capable Multimodal Models

Reference 10

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Observation 58da7911-9ce8-4178-92c6-8288b1130296 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 11

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Observation c4b20dc8-0a92-45e5-88c5-9121e1121338 · outbound

This paper cites The l arger the merrier? Efficient Large AI model inference in wireless edge networks,.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs The l arger the merrier? Efficient Large AI model inference in wireless edge networks,

Reference 12

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Observation b58f4170-3736-4c57-9a56-257812270dc4 · outbound

This paper cites Optimal AI model splitting and resource allocation for device-edge co-inference in multi-user wireless sensing s ystems,.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Optimal AI model splitting and resource allocation for device-edge co-inference in multi-user wireless sensing s ystems,

Reference 13

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation b91b8796-d9b8-45a3-8520-9c596bc4b8f6 · outbound

This paper cites Large language m odels (llms) inference offloading and resource allocation in clou d-edge com- puting: An active inference approach,.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Large language m odels (llms) inference offloading and resource allocation in clou d-edge com- puting: An active inference approach,

Reference 14

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation e76976dc-dc2b-4ada-8b53-5ad82bb2dcc6 · outbound

This paper cites Mcg-sched: Mu lti- cluster gpu scheduling for resource fragmentation reducti on and load balancing,.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Mcg-sched: Mu lti- cluster gpu scheduling for resource fragmentation reducti on and load balancing,

Reference 15

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 21b2fee1-de92-4d5b-b8e4-5c3fa1a8ba70 · outbound

This paper cites Semantic communi cations for image recovery and classification via deep joint source a nd channel coding,.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Semantic communi cations for image recovery and classification via deep joint source a nd channel coding,

Reference 16

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 57787b19-7039-452b-9711-cacdb5044b5d · outbound

This paper cites Semantic communi cation: A survey on research landscape, challenges, and future direc tions,.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Semantic communi cation: A survey on research landscape, challenges, and future direc tions,

Reference 17

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation d5df53c0-1056-43c7-a988-3122a7537857 · outbound

This paper cites Adaptable semanti c compression and resource allocation for task-oriented communications ,.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Adaptable semanti c compression and resource allocation for task-oriented communications ,

Reference 18

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation b3a29014-d9ce-4648-baab-88c477a5a856 · outbound

This paper cites Semantic communication meets edge intelligence : Semantic- relay-aided text transmissions,.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Semantic communication meets edge intelligence : Semantic- relay-aided text transmissions,

Reference 19

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation aefa74a5-1a11-4b6e-b07a-eed43ce6b12a · outbound

This paper cites Optimal model placeme nt and online model splitting for device-edge co-inference,.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Optimal model placeme nt and online model splitting for device-edge co-inference,

Reference 20

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation f66a6cc2-0828-4044-b1ae-42ca88ca61cb · outbound

This paper cites Task- oriented sensing, computation, and communication integra tion for multi- device edge AI,.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Task- oriented sensing, computation, and communication integra tion for multi- device edge AI,

Reference 21

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 5fd0a214-9a31-4467-aff9-4f2a050b86c3 · outbound

This paper cites Beyond the cloud: Edge inference for generativ e large language models in wireless networks,.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Beyond the cloud: Edge inference for generativ e large language models in wireless networks,

Reference 22

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 4657b477-7dbf-4877-8d33-6d4b482daae4 · outbound

This paper cites Adaptive Layer Splitting for Wireless LLM Inference in Edge Computing: A Model-Based Reinforcement Learning Approach.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Adaptive Layer Splitting for Wireless LLM Inference in Edge Computing: A Model-Based Reinforcement Learning Approach

Reference 23

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Unavailable: canonical work link unavailable.

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Observation 1f1d496c-59d2-4303-833f-8b410abe12cd · outbound

This paper cites EdgeShar d: Efficient LLM inference via collaborative edge computing,.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs EdgeShar d: Efficient LLM inference via collaborative edge computing,

Reference 24

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 688373cc-3d95-4872-be64-93e279e17ee4 · outbound

This paper cites Joint inference offloading and model caching for small and large language mod el collaboration,.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Joint inference offloading and model caching for small and large language mod el collaboration,

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 2cbe9f2f-ec8e-4212-a108-f746e33d0876 · outbound

This paper cites Quantization-aware collaborative inference for large em bodied ai mod- els,.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Quantization-aware collaborative inference for large em bodied ai mod- els,

Reference 26

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 5f0e0287-8fea-46ef-9da6-e82cf71d03fc · outbound

This paper cites Jppo++: Join t power and denoising-inspired prompt optimization for mobile llm ser vices,.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Jppo++: Join t power and denoising-inspired prompt optimization for mobile llm ser vices,

Reference 27

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 1e285754-efee-481d-bfdd-18294ca8c420 · outbound

This paper cites Berger, Rate-distortion theory.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Berger, Rate-distortion theory

Reference 28

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation ecc3c500-fcdb-4b31-b27c-d040cb28a315 · outbound

This paper cites an unresolved cited work.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Unresolved cited work

Reference 29

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 8cbfa894-b161-43ae-80ee-d64de2029237 · outbound

This paper cites Data shapley: Equitable valuat ion of data for machine learning,.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Data shapley: Equitable valuat ion of data for machine learning,

Reference 30

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 369811a6-3ed9-46b2-b1d9-9950eae97fbc · outbound

This paper cites Optimization.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Optimization

Reference 31

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 679fa095-9678-4e7a-b982-dc30637f1994 · outbound

This paper cites Boyd and L.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Boyd and L

Reference 32

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 5399ab4a-de4f-44b7-8cfc-24de596f177a · outbound

This paper cites CVX: Matlab software for discipli ned convex programming,.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs CVX: Matlab software for discipli ned convex programming,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:20:56.830158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 83ebe54a-1e90-4e79-a987-9b5f49008bf7 · outbound

This paper cites Task-oriented communica tion for mul- tidevice cooperative edge inference,.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Task-oriented communica tion for mul- tidevice cooperative edge inference,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:20:56.814935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T04:20:56.511354Z digest=sha256:436c4625acbea15fedec1aceb367971a41d06253bc758ecee48a94b242db3a17

Observation c07eadee-88cb-4d37-8f26-29c69a519e64 · outbound

This paper cites MSR-VTT: A large video d escription dataset for bridging video and language,.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs MSR-VTT: A large video d escription dataset for bridging video and language,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:20:56.800643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T04:20:56.515612Z digest=sha256:b14f8418386eae590a2c0df6c6a50f2ce0f5e6a10e081e53246989d9ae03da73

Observation 5e9f56fb-127c-4e3f-baa0-7d319ca2970a · outbound

This paper cites TinyViT: Fast pretraining distillation for small vision t ransformers,.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs TinyViT: Fast pretraining distillation for small vision t ransformers,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:20:56.786637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T04:20:56.519888Z digest=sha256:05658b3f227a56ecf40a4e0ed90b713b024e3368165254b513c6a25e8d3053b8

Observation 6b444cb4-369f-45da-8aa8-24851d0e3046 · outbound

This paper cites Qwen3 Technical Report.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Qwen3 Technical Report

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-08T04:20:56.523974Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T04:20:56.523974Z digest=sha256:40712798dfa14696286bf3df18ecb7fadfea9ad2cf5a37f979046cb0cef0e752

Observation 16f2a7b6-7fe8-4d00-b13b-665e4d1de278 · outbound

This paper cites BLEU: A m ethod for automatic evaluation of machine translation,.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs BLEU: A m ethod for automatic evaluation of machine translation,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:20:56.772220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T04:20:56.528640Z digest=sha256:d93824a5ea38d7365d499d179ab8c43381f787e9d92e38274b09253bf4abba1f

Observation a20bfd58-8ecf-40c6-be59-9af2060817a8 · outbound

This paper cites CIDEr: Conse nsus-based image description evaluation,.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs CIDEr: Conse nsus-based image description evaluation,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:20:56.757844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T04:20:56.532751Z digest=sha256:6ab75dface09f8224abfad438f13e8ac6c899762d247ef6744c0bcc51daa078c

Observation 89cbfa6f-61dc-4232-bfb7-5bd150a903e5 · outbound

This paper cites Available: https://arxiv.org/abs/2511.

Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs Available: https://arxiv.org/abs/2511

Reference 2025

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:20:57.103310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T04:20:56.405871Z digest=sha256:4097d6f467602a2db19ab1eefe404ced4419be79140219c3b964147e2b737d09

Pith citing papers

No inbound Pith citation observations are available.