{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:D4C757JZABWBSFCVPCYAFGYBFK","short_pith_number":"pith:D4C757JZ","canonical_record":{"source":{"id":"1910.02898","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.soft","submitted_at":"2019-10-07T16:40:02Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"a4b96af93f4700f8c16b9356bda1210483a4a1b39c741f57877d70f7e24fd6bf","abstract_canon_sha256":"d92612ddbe939593aec081e6f6a439dd9ff3e46514be1a80f92fe74de38adc56"},"schema_version":"1.0"},"canonical_sha256":"1f05fefd39006c19145578b0029b012aa0da26ee995d6e1b12c8d034c81f0172","source":{"kind":"arxiv","id":"1910.02898","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1910.02898","created_at":"2026-07-05T00:10:12Z"},{"alias_kind":"arxiv_version","alias_value":"1910.02898v1","created_at":"2026-07-05T00:10:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1910.02898","created_at":"2026-07-05T00:10:12Z"},{"alias_kind":"pith_short_12","alias_value":"D4C757JZABWB","created_at":"2026-07-05T00:10:12Z"},{"alias_kind":"pith_short_16","alias_value":"D4C757JZABWBSFCV","created_at":"2026-07-05T00:10:12Z"},{"alias_kind":"pith_short_8","alias_value":"D4C757JZ","created_at":"2026-07-05T00:10:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:D4C757JZABWBSFCVPCYAFGYBFK","target":"record","payload":{"canonical_record":{"source":{"id":"1910.02898","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.soft","submitted_at":"2019-10-07T16:40:02Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"a4b96af93f4700f8c16b9356bda1210483a4a1b39c741f57877d70f7e24fd6bf","abstract_canon_sha256":"d92612ddbe939593aec081e6f6a439dd9ff3e46514be1a80f92fe74de38adc56"},"schema_version":"1.0"},"canonical_sha256":"1f05fefd39006c19145578b0029b012aa0da26ee995d6e1b12c8d034c81f0172","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:10:12.297340Z","signature_b64":"fE8eoxY1g/NsFZZMe07H9la4pynxq9CdZH2/xxSIKltFJiSNT82C1NIb6zK+2L/JRCgAyIAdb1nfpn3uKhVADQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1f05fefd39006c19145578b0029b012aa0da26ee995d6e1b12c8d034c81f0172","last_reissued_at":"2026-07-05T00:10:12.296981Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:10:12.296981Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1910.02898","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T00:10:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"j6RNi48ioK0Qthv02TC135rKzyrOQ55sPK2WEX8pmqC+CNDOTmCriH8Al2wwmDBud4E4Gs4JB8pvzxNhrQF6AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-09T06:03:06.983680Z"},"content_sha256":"d5c358d8ac771317af49cb998c729582d70fe6bf735ba0318787ef30172aebdb","schema_version":"1.0","event_id":"sha256:d5c358d8ac771317af49cb998c729582d70fe6bf735ba0318787ef30172aebdb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:D4C757JZABWBSFCVPCYAFGYBFK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Fast Fitting of Reflectivity Data of Growing Thin Films Using Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cond-mat.soft","authors_text":"Alessandro Greco, Alexander Gerlach, Alexander Hinderhofer, Christos Karapanagiotis, Frank Schreiber, Linus Pithan, Sascha Liehr, Stefan Kowarik, Vladimir Starostin","submitted_at":"2019-10-07T16:40:02Z","abstract_excerpt":"X-ray reflectivity (XRR) is a powerful and popular scattering technique that can give valuable insight into the growth behavior of thin films. In this study, we show how a simple artificial neural network model can be used to predict the thickness, roughness and density of thin films of different organic semiconductors (diindenoperylene, copper(II) phthalocyanine and $\\alpha$-sexithiophene) on silica from their XRR data with millisecond computation time and with minimal user input or a priori knowledge. For a large experimental dataset of 372 XRR curves, we show that a simple fully connected m"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1910.02898","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/1910.02898/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T00:10:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SdV4Jk3l0scrH8q/KqDAZ7b1Uxrj/XSUesxo6vBI2CqnNGbL6Lhl3Ej7u3K5kULDh/6YiCyTDWdzelhmqwsyAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-09T06:03:06.984073Z"},"content_sha256":"57bef67a34666618b4033cbfbf286071ebde095c65cd543a1e4cc6f18e9f0081","schema_version":"1.0","event_id":"sha256:57bef67a34666618b4033cbfbf286071ebde095c65cd543a1e4cc6f18e9f0081"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/D4C757JZABWBSFCVPCYAFGYBFK/bundle.json","state_url":"https://pith.science/pith/D4C757JZABWBSFCVPCYAFGYBFK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/D4C757JZABWBSFCVPCYAFGYBFK/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-09T06:03:06Z","links":{"resolver":"https://pith.science/pith/D4C757JZABWBSFCVPCYAFGYBFK","bundle":"https://pith.science/pith/D4C757JZABWBSFCVPCYAFGYBFK/bundle.json","state":"https://pith.science/pith/D4C757JZABWBSFCVPCYAFGYBFK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/D4C757JZABWBSFCVPCYAFGYBFK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:D4C757JZABWBSFCVPCYAFGYBFK","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":"d92612ddbe939593aec081e6f6a439dd9ff3e46514be1a80f92fe74de38adc56","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.soft","submitted_at":"2019-10-07T16:40:02Z","title_canon_sha256":"a4b96af93f4700f8c16b9356bda1210483a4a1b39c741f57877d70f7e24fd6bf"},"schema_version":"1.0","source":{"id":"1910.02898","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1910.02898","created_at":"2026-07-05T00:10:12Z"},{"alias_kind":"arxiv_version","alias_value":"1910.02898v1","created_at":"2026-07-05T00:10:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1910.02898","created_at":"2026-07-05T00:10:12Z"},{"alias_kind":"pith_short_12","alias_value":"D4C757JZABWB","created_at":"2026-07-05T00:10:12Z"},{"alias_kind":"pith_short_16","alias_value":"D4C757JZABWBSFCV","created_at":"2026-07-05T00:10:12Z"},{"alias_kind":"pith_short_8","alias_value":"D4C757JZ","created_at":"2026-07-05T00:10:12Z"}],"graph_snapshots":[{"event_id":"sha256:57bef67a34666618b4033cbfbf286071ebde095c65cd543a1e4cc6f18e9f0081","target":"graph","created_at":"2026-07-05T00:10:12Z","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/1910.02898/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"X-ray reflectivity (XRR) is a powerful and popular scattering technique that can give valuable insight into the growth behavior of thin films. In this study, we show how a simple artificial neural network model can be used to predict the thickness, roughness and density of thin films of different organic semiconductors (diindenoperylene, copper(II) phthalocyanine and $\\alpha$-sexithiophene) on silica from their XRR data with millisecond computation time and with minimal user input or a priori knowledge. For a large experimental dataset of 372 XRR curves, we show that a simple fully connected m","authors_text":"Alessandro Greco, Alexander Gerlach, Alexander Hinderhofer, Christos Karapanagiotis, Frank Schreiber, Linus Pithan, Sascha Liehr, Stefan Kowarik, Vladimir Starostin","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.soft","submitted_at":"2019-10-07T16:40:02Z","title":"Fast Fitting of Reflectivity Data of Growing Thin Films Using Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1910.02898","kind":"arxiv","version":1},"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:d5c358d8ac771317af49cb998c729582d70fe6bf735ba0318787ef30172aebdb","target":"record","created_at":"2026-07-05T00:10:12Z","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":"d92612ddbe939593aec081e6f6a439dd9ff3e46514be1a80f92fe74de38adc56","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.soft","submitted_at":"2019-10-07T16:40:02Z","title_canon_sha256":"a4b96af93f4700f8c16b9356bda1210483a4a1b39c741f57877d70f7e24fd6bf"},"schema_version":"1.0","source":{"id":"1910.02898","kind":"arxiv","version":1}},"canonical_sha256":"1f05fefd39006c19145578b0029b012aa0da26ee995d6e1b12c8d034c81f0172","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1f05fefd39006c19145578b0029b012aa0da26ee995d6e1b12c8d034c81f0172","first_computed_at":"2026-07-05T00:10:12.296981Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:10:12.296981Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"fE8eoxY1g/NsFZZMe07H9la4pynxq9CdZH2/xxSIKltFJiSNT82C1NIb6zK+2L/JRCgAyIAdb1nfpn3uKhVADQ==","signature_status":"signed_v1","signed_at":"2026-07-05T00:10:12.297340Z","signed_message":"canonical_sha256_bytes"},"source_id":"1910.02898","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d5c358d8ac771317af49cb998c729582d70fe6bf735ba0318787ef30172aebdb","sha256:57bef67a34666618b4033cbfbf286071ebde095c65cd543a1e4cc6f18e9f0081"],"state_sha256":"bc6e673962f36e1ee6dd518b71bc39d6596911634c3a5fef19d1e6f1accb5c7e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"djeEzJD6uxsTWfWy5sYGRMHsVsWRfZCWaaf5j7SiqUnUhj7Byekqu58XQwc7cCQlmCKrTeHI+Snhj84d+5NcAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-09T06:03:06.987637Z","bundle_sha256":"e3b72bf98a1dd97d085cac29f426b8b697b814b1fafe93c7249bd3c1cd1909bf"}}