{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:CGFXJ5WVHDFRKKAZ73W2R2HEEY","short_pith_number":"pith:CGFXJ5WV","canonical_record":{"source":{"id":"1704.04688","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-04-15T20:49:09Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"6702c3a2e386b8c076774015a73c41d73b9ae2ab84ab4d6439957abcf2e6486e","abstract_canon_sha256":"79f591b85192f750c0207bfaad6fa5114e0850dcc4ae9e93f26cb9ad15cf5529"},"schema_version":"1.0"},"canonical_sha256":"118b74f6d538cb152819feeda8e8e426002e991b237bb1718c2aaac798742750","source":{"kind":"arxiv","id":"1704.04688","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1704.04688","created_at":"2026-05-18T00:46:17Z"},{"alias_kind":"arxiv_version","alias_value":"1704.04688v1","created_at":"2026-05-18T00:46:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1704.04688","created_at":"2026-05-18T00:46:17Z"},{"alias_kind":"pith_short_12","alias_value":"CGFXJ5WVHDFR","created_at":"2026-05-18T12:31:10Z"},{"alias_kind":"pith_short_16","alias_value":"CGFXJ5WVHDFRKKAZ","created_at":"2026-05-18T12:31:10Z"},{"alias_kind":"pith_short_8","alias_value":"CGFXJ5WV","created_at":"2026-05-18T12:31:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:CGFXJ5WVHDFRKKAZ73W2R2HEEY","target":"record","payload":{"canonical_record":{"source":{"id":"1704.04688","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-04-15T20:49:09Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"6702c3a2e386b8c076774015a73c41d73b9ae2ab84ab4d6439957abcf2e6486e","abstract_canon_sha256":"79f591b85192f750c0207bfaad6fa5114e0850dcc4ae9e93f26cb9ad15cf5529"},"schema_version":"1.0"},"canonical_sha256":"118b74f6d538cb152819feeda8e8e426002e991b237bb1718c2aaac798742750","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:46:17.942448Z","signature_b64":"jGhyD6mRYIJ0LHAoN5nARtXHnJ7rjLFwPqr5fHNyy12MjBwFJB9cCqknPv7/1UZAHHHEw1FDj0dmFIRSrbDxDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"118b74f6d538cb152819feeda8e8e426002e991b237bb1718c2aaac798742750","last_reissued_at":"2026-05-18T00:46:17.942079Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:46:17.942079Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1704.04688","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":"2026-05-18T00:46:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Q2vJ7XzG+J2mtdYIHayRPKtWEOUx7F3Y3l6ankhjxtnUL4FsX6bsljNSzjS3xmvIf8ZY55BalhruKEo7/+oJCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T18:09:53.284775Z"},"content_sha256":"ff38c6631c3fe7850e25faef51d5dfbc498c968a77e1856dd549e30678c9686e","schema_version":"1.0","event_id":"sha256:ff38c6631c3fe7850e25faef51d5dfbc498c968a77e1856dd549e30678c9686e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:CGFXJ5WVHDFRKKAZ73W2R2HEEY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Machine Learning and the Future of Realism","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Cliff Hooker, Giles Hooker","submitted_at":"2017-04-15T20:49:09Z","abstract_excerpt":"The preceding three decades have seen the emergence, rise, and proliferation of machine learning (ML). From half-recognised beginnings in perceptrons, neural nets, and decision trees, algorithms that extract correlations (that is, patterns) from a set of data points have broken free from their origin in computational cognition to embrace all forms of problem solving, from voice recognition to medical diagnosis to automated scientific research and driverless cars, and it is now widely opined that the real industrial revolution lies less in mobile phone and similar than in the maturation and uni"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1704.04688","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":""},"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":"2026-05-18T00:46:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vMFDebhdugoTeBHRgOahMDmXXIdoJ5NnUlsSZRRkdqV9Yr3dSNKCvQXgjEUnbfM9aEhlX9UdewAfW/MHuuisDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T18:09:53.285488Z"},"content_sha256":"c58449c2d18a2c6284c7ccd33d60834040446a29adcc8348bd00a9146f44c431","schema_version":"1.0","event_id":"sha256:c58449c2d18a2c6284c7ccd33d60834040446a29adcc8348bd00a9146f44c431"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CGFXJ5WVHDFRKKAZ73W2R2HEEY/bundle.json","state_url":"https://pith.science/pith/CGFXJ5WVHDFRKKAZ73W2R2HEEY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CGFXJ5WVHDFRKKAZ73W2R2HEEY/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":"2026-05-26T18:09:53Z","links":{"resolver":"https://pith.science/pith/CGFXJ5WVHDFRKKAZ73W2R2HEEY","bundle":"https://pith.science/pith/CGFXJ5WVHDFRKKAZ73W2R2HEEY/bundle.json","state":"https://pith.science/pith/CGFXJ5WVHDFRKKAZ73W2R2HEEY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CGFXJ5WVHDFRKKAZ73W2R2HEEY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:CGFXJ5WVHDFRKKAZ73W2R2HEEY","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":"79f591b85192f750c0207bfaad6fa5114e0850dcc4ae9e93f26cb9ad15cf5529","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-04-15T20:49:09Z","title_canon_sha256":"6702c3a2e386b8c076774015a73c41d73b9ae2ab84ab4d6439957abcf2e6486e"},"schema_version":"1.0","source":{"id":"1704.04688","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1704.04688","created_at":"2026-05-18T00:46:17Z"},{"alias_kind":"arxiv_version","alias_value":"1704.04688v1","created_at":"2026-05-18T00:46:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1704.04688","created_at":"2026-05-18T00:46:17Z"},{"alias_kind":"pith_short_12","alias_value":"CGFXJ5WVHDFR","created_at":"2026-05-18T12:31:10Z"},{"alias_kind":"pith_short_16","alias_value":"CGFXJ5WVHDFRKKAZ","created_at":"2026-05-18T12:31:10Z"},{"alias_kind":"pith_short_8","alias_value":"CGFXJ5WV","created_at":"2026-05-18T12:31:10Z"}],"graph_snapshots":[{"event_id":"sha256:c58449c2d18a2c6284c7ccd33d60834040446a29adcc8348bd00a9146f44c431","target":"graph","created_at":"2026-05-18T00:46:17Z","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"},"paper":{"abstract_excerpt":"The preceding three decades have seen the emergence, rise, and proliferation of machine learning (ML). From half-recognised beginnings in perceptrons, neural nets, and decision trees, algorithms that extract correlations (that is, patterns) from a set of data points have broken free from their origin in computational cognition to embrace all forms of problem solving, from voice recognition to medical diagnosis to automated scientific research and driverless cars, and it is now widely opined that the real industrial revolution lies less in mobile phone and similar than in the maturation and uni","authors_text":"Cliff Hooker, Giles Hooker","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-04-15T20:49:09Z","title":"Machine Learning and the Future of Realism"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1704.04688","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:ff38c6631c3fe7850e25faef51d5dfbc498c968a77e1856dd549e30678c9686e","target":"record","created_at":"2026-05-18T00:46:17Z","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":"79f591b85192f750c0207bfaad6fa5114e0850dcc4ae9e93f26cb9ad15cf5529","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-04-15T20:49:09Z","title_canon_sha256":"6702c3a2e386b8c076774015a73c41d73b9ae2ab84ab4d6439957abcf2e6486e"},"schema_version":"1.0","source":{"id":"1704.04688","kind":"arxiv","version":1}},"canonical_sha256":"118b74f6d538cb152819feeda8e8e426002e991b237bb1718c2aaac798742750","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"118b74f6d538cb152819feeda8e8e426002e991b237bb1718c2aaac798742750","first_computed_at":"2026-05-18T00:46:17.942079Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:46:17.942079Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"jGhyD6mRYIJ0LHAoN5nARtXHnJ7rjLFwPqr5fHNyy12MjBwFJB9cCqknPv7/1UZAHHHEw1FDj0dmFIRSrbDxDw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:46:17.942448Z","signed_message":"canonical_sha256_bytes"},"source_id":"1704.04688","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ff38c6631c3fe7850e25faef51d5dfbc498c968a77e1856dd549e30678c9686e","sha256:c58449c2d18a2c6284c7ccd33d60834040446a29adcc8348bd00a9146f44c431"],"state_sha256":"4d66f1415ff87f8fdf592fd1a49530d1435a2131071ec2dbca14acb310ef020f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SZzmdn78j+qGy0ZWhfxzjfZiQP+pTRhoozPN44oGVprBNW/gdV60AaowSOPUvjKOTB4Kv9jRHziA5FpCKbetBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T18:09:53.289170Z","bundle_sha256":"f5843f307a125508ff70583c116ff582ac441195b3f8438e599e2e320bb84e33"}}