Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-08T14:55:49.896718Z
Paper Citation Record · LEDGER
As of 10 August 2026, this Paper Citation Record lists 10 of 10 outbound references and 0 inbound Pith citation observations for arXiv:2502.06920.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-08T14:55:49.896718Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
10 of 10 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 521684e6-07e0-426c-a888-f26bf31fa4f9 · outbound
Direct Estimation of Pediatric Heart Rate Variability from BOLD-fMRI: A Machine Learning Approach Using Dynamic Connectivity Unresolved cited work
Reference 1
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 8c35ff88-e31b-47fa-af31-ebde7186d25c · outbound
Direct Estimation of Pediatric Heart Rate Variability from BOLD-fMRI: A Machine Learning Approach Using Dynamic Connectivity Extending the Human Connectome Project across ages: Imaging protocols for the Lifespan Development and Aging projects,
Reference 2
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 60259969-4e44-4132-bb52-7612d0fa8ecd · outbound
Direct Estimation of Pediatric Heart Rate Variability from BOLD-fMRI: A Machine Learning Approach Using Dynamic Connectivity HRV is estimated from a 65 TR sliding window at the 10th point, utilizing past and future data to capture the inherent dynamic fluctuations, typically around 40 seconds
Reference 3
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation fcc4e8e0-2584-4cdc-838a-28fe36c4db9f · outbound
Direct Estimation of Pediatric Heart Rate Variability from BOLD-fMRI: A Machine Learning Approach Using Dynamic Connectivity It compares measured and model-reconstructed HRV waveforms in three test cases (a, b, c), with corresponding MAE, MSE, Pearson correlation (r), and DTW values highlighted
Reference 4
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 778be41b-b828-4cf9-ae54-9b67825895de · outbound
Direct Estimation of Pediatric Heart Rate Variability from BOLD-fMRI: A Machine Learning Approach Using Dynamic Connectivity This figure presents violin plots depicting the performance of the machine learning model in reconstructing HRV across various input configurations
Reference 5
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation a5b0df90-b6f4-411f-ad7d-b1ad7bd18de2 · outbound
Direct Estimation of Pediatric Heart Rate Variability from BOLD-fMRI: A Machine Learning Approach Using Dynamic Connectivity Unresolved cited work
Reference 6
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation afd7c290-0f70-4ebf-848a-0d30ff845902 · outbound
Direct Estimation of Pediatric Heart Rate Variability from BOLD-fMRI: A Machine Learning Approach Using Dynamic Connectivity Direct machine learning reconstruction of respiratory variation waveforms from resting state fMRI data in a pediatric population,
Reference 7
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f84bb999-9f9f-4ea9-adbe-b97793f4c813 · outbound
Direct Estimation of Pediatric Heart Rate Variability from BOLD-fMRI: A Machine Learning Approach Using Dynamic Connectivity Low-frequency fluctuations in the cardiac rate as a source of variance in the resting-state fMRI BOLD signal,
Reference 8
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation cc1016ef-4e3b-40d5-8f68-49a08efad19e · outbound
Direct Estimation of Pediatric Heart Rate Variability from BOLD-fMRI: A Machine Learning Approach Using Dynamic Connectivity Mapping the end-tidal CO2 response function in the resting-state BOLD fMRI signal: Spatial specificity, test–retest reliability and effect of fMRI sampling rate,
Reference 9
Source-reported events for the cited work
correction dated 2017-11-07. Source: crossref record 10.1016/j.neuroimage.2017.10.061->10.1016/j.neuroimage.2014.10.031:correction, observed 2026-07-11T03:18:37.16385+00:00. This notice travels one citation hop only.
Observation 0dfa64cc-8fc5-41e8-8116-5f238f0c0a8a · outbound
Direct Estimation of Pediatric Heart Rate Variability from BOLD-fMRI: A Machine Learning Approach Using Dynamic Connectivity A c o m p o n e n t b a s e d n o i s e c o r r e c t i o n m e t h o d ( C o m p C o r ) f o r BOLD and perfusion based fMRI,
Reference 10
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
No inbound Pith citation observations are available.