Pith. sign in

Integrity report for Physics-Data Driven Machine Learning Based Model: A Hybrid Way for Nonlinear, Dynamic, and Open-loop Identification of IPMC Soft Artificial Muscles

A machine-verified record of the checks Pith has run against this paper: detector runs, findings, signed bundle events, and canonical identifiers.

arXiv:2203.01616 · pith:2022:D4ZCD7TYK6ELCXXNZDL6ZMBRCH

0Critical
0Advisory
0Detectors run
Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

Findings

No public integrity findings for this paper.

Signed record

The machine-readable record for this paper lives at /pith/D4ZCD7TY/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.