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Integrity report for AirPhyNet: Harnessing Physics-Guided Neural Networks for Air Quality Prediction

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

arXiv:2402.03784 · pith:2024:2WC2UAEGW3JYUC2AHSS7V2B3UY

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Paper page arXiv integrity.json bundle.json

Detector runs

Findings

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Signed record

The machine-readable record for this paper lives at /pith/2WC2UAEG/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.