Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T14:25:53.707560Z
Paper Citation Record · LEDGER
Integrating Dynamical Systems Learning with Foundational Models: A Meta-Evolutionary AI Framework for Clinical Trials
As of 21 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 1 inbound Pith citation observation for arXiv:2506.14782.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-26T04:40:48.487348Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T13:59:52.662311Z
Reference resolution
17 of 17 outbound references displayed
- verified exact0
- verified fuzzy5
- unresolved12
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 75fd534a-3c2d-4958-ad56-489725cb1e85 · outbound
This paper cites https://www.nobelprize.org/prizes/chemistry/2024/ hassabis/lecture/.
Integrating Dynamical Systems Learning with Foundational Models: A Meta-Evolutionary AI Framework for Clinical Trials https://www.nobelprize.org/prizes/chemistry/2024/ hassabis/lecture/
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:25:55.780981Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation afbf067f-5cd4-4112-bbe8-7d3dd3091321 · outbound
This paper cites https://huggingface.co/deepseek-ai/DeepSeek-V3.
Integrating Dynamical Systems Learning with Foundational Models: A Meta-Evolutionary AI Framework for Clinical Trials https://huggingface.co/deepseek-ai/DeepSeek-V3
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:25:55.643074Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 6c8891b7-526e-433a-ac07-09c437ad40c8 · outbound
This paper cites Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead.Nat Mach Intell1, 206–215 (2019).
Integrating Dynamical Systems Learning with Foundational Models: A Meta-Evolutionary AI Framework for Clinical Trials Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead.Nat Mach Intell1, 206–215 (2019)
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:25:55.564899Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 1726c5f0-a586-4dc5-9978-ea3d9bf84a87 · outbound
This paper cites an unresolved cited work.
Integrating Dynamical Systems Learning with Foundational Models: A Meta-Evolutionary AI Framework for Clinical Trials Unresolved cited work
Reference 4
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T14:25:55.393609Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 5095ff94-f893-47e3-91cd-1c02bbeea6f2 · outbound
This paper cites an unresolved cited work.
Integrating Dynamical Systems Learning with Foundational Models: A Meta-Evolutionary AI Framework for Clinical Trials Unresolved cited work
Reference 5
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T14:25:55.281757Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 27c0f10a-ebdb-4ef2-8583-8969f62d6e4a · outbound
This paper cites & Barak, B.Computational Complexity: A Modern Approach.
Integrating Dynamical Systems Learning with Foundational Models: A Meta-Evolutionary AI Framework for Clinical Trials & Barak, B.Computational Complexity: A Modern Approach
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:25:55.118251Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 6b77033c-d798-4958-b515-7c90d6122be6 · outbound
This paper cites an unresolved cited work.
Integrating Dynamical Systems Learning with Foundational Models: A Meta-Evolutionary AI Framework for Clinical Trials Unresolved cited work
Reference 7
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T14:25:55.011822Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 68caba90-c055-4efd-b723-3447d7febea8 · outbound
This paper cites an unresolved cited work.
Integrating Dynamical Systems Learning with Foundational Models: A Meta-Evolutionary AI Framework for Clinical Trials Unresolved cited work
Reference 8
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T14:25:54.875176Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 268fc527-aded-4bb7-a168-88fb40ef01a6 · outbound
This paper cites https://medium.
Integrating Dynamical Systems Learning with Foundational Models: A Meta-Evolutionary AI Framework for Clinical Trials https://medium
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:25:54.759398Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 07986fae-1a28-4e3e-a2ca-a1fc96e1574b · outbound
This paper cites an unresolved cited work.
Integrating Dynamical Systems Learning with Foundational Models: A Meta-Evolutionary AI Framework for Clinical Trials Unresolved cited work
Reference 10
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T14:25:54.683216Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation cf535dbc-bdd1-436a-b900-ad2653b71d05 · outbound
This paper cites an unresolved cited work.
Integrating Dynamical Systems Learning with Foundational Models: A Meta-Evolutionary AI Framework for Clinical Trials Unresolved cited work
Reference 11
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T14:25:54.589441Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 89a4b7f0-090f-4131-8198-1dcbcf91b4a3 · outbound
This paper cites an unresolved cited work.
Integrating Dynamical Systems Learning with Foundational Models: A Meta-Evolutionary AI Framework for Clinical Trials Unresolved cited work
Reference 12
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T14:25:54.458099Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 93f9697d-e97f-4d5d-8230-705b0c87c467 · outbound
This paper cites an unresolved cited work.
Integrating Dynamical Systems Learning with Foundational Models: A Meta-Evolutionary AI Framework for Clinical Trials Unresolved cited work
Reference 13
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T14:25:54.325789Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 943cbf0e-aeb0-43f6-ad8c-4318a584389a · outbound
This paper cites an unresolved cited work.
Integrating Dynamical Systems Learning with Foundational Models: A Meta-Evolutionary AI Framework for Clinical Trials Unresolved cited work
Reference 14
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T14:25:54.237656Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 454b939b-c10a-4c80-abde-0b8d44d6bd08 · outbound
This paper cites an unresolved cited work.
Integrating Dynamical Systems Learning with Foundational Models: A Meta-Evolutionary AI Framework for Clinical Trials Unresolved cited work
Reference 15
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T14:25:54.095096Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 93bca2ce-80bf-43ba-8283-6460c43e96d5 · outbound
This paper cites an unresolved cited work.
Integrating Dynamical Systems Learning with Foundational Models: A Meta-Evolutionary AI Framework for Clinical Trials Unresolved cited work
Reference 16
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T14:25:53.961352Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 608c4531-72fe-4ea7-ba6d-69d022b7e241 · outbound
This paper cites an unresolved cited work.
Integrating Dynamical Systems Learning with Foundational Models: A Meta-Evolutionary AI Framework for Clinical Trials Unresolved cited work
Reference 17
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T14:25:53.860611Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Pith citing papers
Observation 7ff56728-6902-4fd3-84ac-08583017e837 · inbound
Semantic Early-Stopping for Iterative LLM Agent Loops cites this paper.
Semantic Early-Stopping for Iterative LLM Agent Loops Integrating Dynamical Systems Learning with Foundational Models: A Meta-Evolutionary AI Framework for Clinical Trials
Reference 8
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T13:59:52.663899Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.