{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:JS3AM5K2JLVE42STH6DJ5JBETS","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"0df28bbe1a77e6cfe93ac9bf985678569b572c083e65a2a4b4ee21e6518767d5","cross_cats_sorted":["stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2019-02-17T01:31:58Z","title_canon_sha256":"5d73b3b884a4cc0ab6c081c089cbcc07be4f1d01e1b236ab94ad39ae65315370"},"schema_version":"1.0","source":{"id":"1902.06183","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.06183","created_at":"2026-07-05T00:58:02Z"},{"alias_kind":"arxiv_version","alias_value":"1902.06183v2","created_at":"2026-07-05T00:58:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.06183","created_at":"2026-07-05T00:58:02Z"},{"alias_kind":"pith_short_12","alias_value":"JS3AM5K2JLVE","created_at":"2026-07-05T00:58:02Z"},{"alias_kind":"pith_short_16","alias_value":"JS3AM5K2JLVE42ST","created_at":"2026-07-05T00:58:02Z"},{"alias_kind":"pith_short_8","alias_value":"JS3AM5K2","created_at":"2026-07-05T00:58:02Z"}],"graph_snapshots":[{"event_id":"sha256:76f4f21aa8f2b03cec7eb4204b45ff50ea5237bece4f1819f9bda89b885f3310","target":"graph","created_at":"2026-07-05T00:58:02Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/1902.06183/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Spatial prediction of weather-elements like temperature, precipitation, and barometric pressure are generally based on satellite imagery or data collected at ground-stations. None of these data provide information at a more granular or \"hyper-local\" resolution. On the other hand, crowdsourced weather data, which are captured by sensors installed on mobile devices and gathered by weather-related mobile apps like WeatherSignal and AccuWeather, can serve as potential data sources for analyzing environmental processes at a hyper-local resolution. However, due to the low quality of the sensors and ","authors_text":"Alyson Wilson, Arnab Chakraborty, Soumendra Nath Lahiri","cross_cats":["stat.ME"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2019-02-17T01:31:58Z","title":"A Statistical Analysis of Noisy Crowdsourced Weather Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.06183","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:aa65f1f275a07d5aa96a58b1d00be8eb6a0efe936da26f317194b79e7d021c9b","target":"record","created_at":"2026-07-05T00:58:02Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"0df28bbe1a77e6cfe93ac9bf985678569b572c083e65a2a4b4ee21e6518767d5","cross_cats_sorted":["stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2019-02-17T01:31:58Z","title_canon_sha256":"5d73b3b884a4cc0ab6c081c089cbcc07be4f1d01e1b236ab94ad39ae65315370"},"schema_version":"1.0","source":{"id":"1902.06183","kind":"arxiv","version":2}},"canonical_sha256":"4cb606755a4aea4e6a533f869ea4249c81a5d9407eb5d5fd9d1a6a511d9bd7e7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4cb606755a4aea4e6a533f869ea4249c81a5d9407eb5d5fd9d1a6a511d9bd7e7","first_computed_at":"2026-07-05T00:58:02.156284Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:58:02.156284Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"aFC8VJsqp6OrN8QkM4AYZWSLZFvhKLHPzaN2WjUsWHSrnI6NSXN3KccFSo5bLAn3XKCQs/R5qfu2xwi33BZGCw==","signature_status":"signed_v1","signed_at":"2026-07-05T00:58:02.156712Z","signed_message":"canonical_sha256_bytes"},"source_id":"1902.06183","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:aa65f1f275a07d5aa96a58b1d00be8eb6a0efe936da26f317194b79e7d021c9b","sha256:76f4f21aa8f2b03cec7eb4204b45ff50ea5237bece4f1819f9bda89b885f3310"],"state_sha256":"c214e3a08c9e027f062e09ce31ea164efec3fdc44898c55a81b2e65aadf5de7a"}