{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:7VW6NGEFGFBZCDIZ4JSMPNO3CV","short_pith_number":"pith:7VW6NGEF","canonical_record":{"source":{"id":"1901.01686","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-01-07T07:27:11Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"9e49068c0f5da141fa0c129adfe131bed7bbb6c1118144108636dcf6d512d9cd","abstract_canon_sha256":"9c6bb5aa0a0ea5d04a7d2e1e1ab9dc38910ac8df25d41d8aea793494c9ca8c62"},"schema_version":"1.0"},"canonical_sha256":"fd6de698853143910d19e264c7b5db1551118b456f5f026e193fa8d3e08c2d4c","source":{"kind":"arxiv","id":"1901.01686","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1901.01686","created_at":"2026-05-17T23:56:51Z"},{"alias_kind":"arxiv_version","alias_value":"1901.01686v1","created_at":"2026-05-17T23:56:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.01686","created_at":"2026-05-17T23:56:51Z"},{"alias_kind":"pith_short_12","alias_value":"7VW6NGEFGFBZ","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_16","alias_value":"7VW6NGEFGFBZCDIZ","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_8","alias_value":"7VW6NGEF","created_at":"2026-05-18T12:33:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:7VW6NGEFGFBZCDIZ4JSMPNO3CV","target":"record","payload":{"canonical_record":{"source":{"id":"1901.01686","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-01-07T07:27:11Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"9e49068c0f5da141fa0c129adfe131bed7bbb6c1118144108636dcf6d512d9cd","abstract_canon_sha256":"9c6bb5aa0a0ea5d04a7d2e1e1ab9dc38910ac8df25d41d8aea793494c9ca8c62"},"schema_version":"1.0"},"canonical_sha256":"fd6de698853143910d19e264c7b5db1551118b456f5f026e193fa8d3e08c2d4c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:56:51.456721Z","signature_b64":"cGajbJzhtrrHazcXujytcBCQu4C+96avnESnqJlvtxjh9oBb27ughXvtqep799oCfjoEtUSQsUBu0zxQhy5FBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fd6de698853143910d19e264c7b5db1551118b456f5f026e193fa8d3e08c2d4c","last_reissued_at":"2026-05-17T23:56:51.456365Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:56:51.456365Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1901.01686","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":"2026-05-17T23:56:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BddbcXZ2DqM6nDm/MC9gO6yAPpqMMljW6E+3r1+n+aqd2wOKZZP2s0Y6LCHUMcmsJFRatc2pRRn3phKOgXoNAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T14:28:53.443056Z"},"content_sha256":"8cbca76ba9384bcd52f3e2cfd999d37cc00ebc741a12c5b9914d932abc5575ff","schema_version":"1.0","event_id":"sha256:8cbca76ba9384bcd52f3e2cfd999d37cc00ebc741a12c5b9914d932abc5575ff"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:7VW6NGEFGFBZCDIZ4JSMPNO3CV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Ten ways to fool the masses with machine learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Amina Asif, Asa Ben-Hur, Fayyaz Minhas","submitted_at":"2019-01-07T07:27:11Z","abstract_excerpt":"If you want to tell people the truth, make them laugh, otherwise they'll kill you. (source unclear)\n  Machine learning and deep learning are the technologies of the day for developing intelligent automatic systems. However, a key hurdle for progress in the field is the literature itself: we often encounter papers that report results that are difficult to reconstruct or reproduce, results that mis-represent the performance of the system, or contain other biases that limit their validity. In this semi-humorous article, we discuss issues that arise in running and reporting results of machine lear"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.01686","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":"2026-05-17T23:56:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JriCy8G6GgPfo2rpHj2j7GfyGY3+fC2deJthx1DEFNLCkZPHcujPl+tcAKXcpuEV1uqsOpxpJu/U3cbEmh1zDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T14:28:53.443407Z"},"content_sha256":"11d654f6f5a4a7dcb94c90e7de7c10d7b7dcdbe45992d55466b1e81d90c0eeba","schema_version":"1.0","event_id":"sha256:11d654f6f5a4a7dcb94c90e7de7c10d7b7dcdbe45992d55466b1e81d90c0eeba"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7VW6NGEFGFBZCDIZ4JSMPNO3CV/bundle.json","state_url":"https://pith.science/pith/7VW6NGEFGFBZCDIZ4JSMPNO3CV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7VW6NGEFGFBZCDIZ4JSMPNO3CV/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":"2026-07-06T14:28:53Z","links":{"resolver":"https://pith.science/pith/7VW6NGEFGFBZCDIZ4JSMPNO3CV","bundle":"https://pith.science/pith/7VW6NGEFGFBZCDIZ4JSMPNO3CV/bundle.json","state":"https://pith.science/pith/7VW6NGEFGFBZCDIZ4JSMPNO3CV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7VW6NGEFGFBZCDIZ4JSMPNO3CV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:7VW6NGEFGFBZCDIZ4JSMPNO3CV","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":"9c6bb5aa0a0ea5d04a7d2e1e1ab9dc38910ac8df25d41d8aea793494c9ca8c62","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-01-07T07:27:11Z","title_canon_sha256":"9e49068c0f5da141fa0c129adfe131bed7bbb6c1118144108636dcf6d512d9cd"},"schema_version":"1.0","source":{"id":"1901.01686","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1901.01686","created_at":"2026-05-17T23:56:51Z"},{"alias_kind":"arxiv_version","alias_value":"1901.01686v1","created_at":"2026-05-17T23:56:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.01686","created_at":"2026-05-17T23:56:51Z"},{"alias_kind":"pith_short_12","alias_value":"7VW6NGEFGFBZ","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_16","alias_value":"7VW6NGEFGFBZCDIZ","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_8","alias_value":"7VW6NGEF","created_at":"2026-05-18T12:33:12Z"}],"graph_snapshots":[{"event_id":"sha256:11d654f6f5a4a7dcb94c90e7de7c10d7b7dcdbe45992d55466b1e81d90c0eeba","target":"graph","created_at":"2026-05-17T23:56:51Z","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":"If you want to tell people the truth, make them laugh, otherwise they'll kill you. (source unclear)\n  Machine learning and deep learning are the technologies of the day for developing intelligent automatic systems. However, a key hurdle for progress in the field is the literature itself: we often encounter papers that report results that are difficult to reconstruct or reproduce, results that mis-represent the performance of the system, or contain other biases that limit their validity. In this semi-humorous article, we discuss issues that arise in running and reporting results of machine lear","authors_text":"Amina Asif, Asa Ben-Hur, Fayyaz Minhas","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-01-07T07:27:11Z","title":"Ten ways to fool the masses with machine learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.01686","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":"sha256:8cbca76ba9384bcd52f3e2cfd999d37cc00ebc741a12c5b9914d932abc5575ff","target":"record","created_at":"2026-05-17T23:56:51Z","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":"9c6bb5aa0a0ea5d04a7d2e1e1ab9dc38910ac8df25d41d8aea793494c9ca8c62","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-01-07T07:27:11Z","title_canon_sha256":"9e49068c0f5da141fa0c129adfe131bed7bbb6c1118144108636dcf6d512d9cd"},"schema_version":"1.0","source":{"id":"1901.01686","kind":"arxiv","version":1}},"canonical_sha256":"fd6de698853143910d19e264c7b5db1551118b456f5f026e193fa8d3e08c2d4c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fd6de698853143910d19e264c7b5db1551118b456f5f026e193fa8d3e08c2d4c","first_computed_at":"2026-05-17T23:56:51.456365Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:56:51.456365Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"cGajbJzhtrrHazcXujytcBCQu4C+96avnESnqJlvtxjh9oBb27ughXvtqep799oCfjoEtUSQsUBu0zxQhy5FBA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:56:51.456721Z","signed_message":"canonical_sha256_bytes"},"source_id":"1901.01686","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8cbca76ba9384bcd52f3e2cfd999d37cc00ebc741a12c5b9914d932abc5575ff","sha256:11d654f6f5a4a7dcb94c90e7de7c10d7b7dcdbe45992d55466b1e81d90c0eeba"],"state_sha256":"6e915373802cd5596a6919052cc6f01eb59be0557ea163cf1727157b280e94e6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NPtQA6sMUFFVKavQAmP2GSLIC+f4XIKQjM5pzZmHwq59Qgscxvsnw6WsHpOisb+Ze80eOb+5C5lW2mi/8AsKBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T14:28:53.445444Z","bundle_sha256":"ddd5ac7de4bdbf3df166fe2aaa00e61d67b69a69ee6af166a4b0ff2cb30f2f2c"}}