{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:33CQZHDNWOCVL6K22MH66LI2NS","short_pith_number":"pith:33CQZHDN","canonical_record":{"source":{"id":"1611.05136","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2016-11-16T03:45:12Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"6f701f2b6f0dbdcbfa0a37c8d2516d3c5d2061add4958227aa164cadfca6780a","abstract_canon_sha256":"8c2762760ab354a267d53df6aa018a42387725ca26130afb48d5f3aed71e6012"},"schema_version":"1.0"},"canonical_sha256":"dec50c9c6db38555f95ad30fef2d1a6c8013c6d267505743b71c52c53b70533c","source":{"kind":"arxiv","id":"1611.05136","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1611.05136","created_at":"2026-05-18T00:57:45Z"},{"alias_kind":"arxiv_version","alias_value":"1611.05136v1","created_at":"2026-05-18T00:57:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1611.05136","created_at":"2026-05-18T00:57:45Z"},{"alias_kind":"pith_short_12","alias_value":"33CQZHDNWOCV","created_at":"2026-05-18T12:29:55Z"},{"alias_kind":"pith_short_16","alias_value":"33CQZHDNWOCVL6K2","created_at":"2026-05-18T12:29:55Z"},{"alias_kind":"pith_short_8","alias_value":"33CQZHDN","created_at":"2026-05-18T12:29:55Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:33CQZHDNWOCVL6K22MH66LI2NS","target":"record","payload":{"canonical_record":{"source":{"id":"1611.05136","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2016-11-16T03:45:12Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"6f701f2b6f0dbdcbfa0a37c8d2516d3c5d2061add4958227aa164cadfca6780a","abstract_canon_sha256":"8c2762760ab354a267d53df6aa018a42387725ca26130afb48d5f3aed71e6012"},"schema_version":"1.0"},"canonical_sha256":"dec50c9c6db38555f95ad30fef2d1a6c8013c6d267505743b71c52c53b70533c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:57:45.378621Z","signature_b64":"5kXlZojqIAg//SnqT3h2Q9r9LBpVhdc7vd3KqHRMCaDOCIYX3c0bocGktYjJgVqOT+dKI5wWLEq5B9tJaih0Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dec50c9c6db38555f95ad30fef2d1a6c8013c6d267505743b71c52c53b70533c","last_reissued_at":"2026-05-18T00:57:45.377963Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:57:45.377963Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1611.05136","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":"2026-05-18T00:57:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QTbjpvg0NW9/JZ5q81gVAsUqXO/hH8M98Q1iNYFWLAC/3CYlUTMYu7et030wptmnRgESZBbQ7x+7lj04ELRuBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T08:37:13.721236Z"},"content_sha256":"e853a1ee487039c28df208e06524febd10d6c7033493bf0b00bacff6f77a956d","schema_version":"1.0","event_id":"sha256:e853a1ee487039c28df208e06524febd10d6c7033493bf0b00bacff6f77a956d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:33CQZHDNWOCVL6K22MH66LI2NS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Machine Learning Approach for Skill Evaluation in Robotic-Assisted Surgery","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Abhilash K. Pandya, Mahtab J. Fard, Michael D. Klein, Ratna B. Chinnam, R. Darin Ellis, Sattar Ameri","submitted_at":"2016-11-16T03:45:12Z","abstract_excerpt":"Evaluating surgeon skill has predominantly been a subjective task. Development of objective methods for surgical skill assessment are of increased interest. Recently, with technological advances such as robotic-assisted minimally invasive surgery (RMIS), new opportunities for objective and automated assessment frameworks have arisen. In this paper, we applied machine learning methods to automatically evaluate performance of the surgeon in RMIS. Six important movement features were used in the evaluation including completion time, path length, depth perception, speed, smoothness and curvature. "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1611.05136","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":"2026-05-18T00:57:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BVVstgqAv5vbHk4F/xMwxVWV1oc4xG7xzMs3+dqqsHPCr7UA8q3sxsDHIgs2x1ekGB8ClfKLDJ8IJhZNcu2zCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T08:37:13.721701Z"},"content_sha256":"7eb77e3bcdf0e52836c5b9c85ad0cd5ba7fa96fef4f6b03c3ef6b23a29f1234b","schema_version":"1.0","event_id":"sha256:7eb77e3bcdf0e52836c5b9c85ad0cd5ba7fa96fef4f6b03c3ef6b23a29f1234b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/33CQZHDNWOCVL6K22MH66LI2NS/bundle.json","state_url":"https://pith.science/pith/33CQZHDNWOCVL6K22MH66LI2NS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/33CQZHDNWOCVL6K22MH66LI2NS/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":"2026-08-12T08:37:13Z","links":{"resolver":"https://pith.science/pith/33CQZHDNWOCVL6K22MH66LI2NS","bundle":"https://pith.science/pith/33CQZHDNWOCVL6K22MH66LI2NS/bundle.json","state":"https://pith.science/pith/33CQZHDNWOCVL6K22MH66LI2NS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/33CQZHDNWOCVL6K22MH66LI2NS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:33CQZHDNWOCVL6K22MH66LI2NS","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":"8c2762760ab354a267d53df6aa018a42387725ca26130afb48d5f3aed71e6012","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2016-11-16T03:45:12Z","title_canon_sha256":"6f701f2b6f0dbdcbfa0a37c8d2516d3c5d2061add4958227aa164cadfca6780a"},"schema_version":"1.0","source":{"id":"1611.05136","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1611.05136","created_at":"2026-05-18T00:57:45Z"},{"alias_kind":"arxiv_version","alias_value":"1611.05136v1","created_at":"2026-05-18T00:57:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1611.05136","created_at":"2026-05-18T00:57:45Z"},{"alias_kind":"pith_short_12","alias_value":"33CQZHDNWOCV","created_at":"2026-05-18T12:29:55Z"},{"alias_kind":"pith_short_16","alias_value":"33CQZHDNWOCVL6K2","created_at":"2026-05-18T12:29:55Z"},{"alias_kind":"pith_short_8","alias_value":"33CQZHDN","created_at":"2026-05-18T12:29:55Z"}],"graph_snapshots":[{"event_id":"sha256:7eb77e3bcdf0e52836c5b9c85ad0cd5ba7fa96fef4f6b03c3ef6b23a29f1234b","target":"graph","created_at":"2026-05-18T00:57:45Z","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":"Evaluating surgeon skill has predominantly been a subjective task. Development of objective methods for surgical skill assessment are of increased interest. Recently, with technological advances such as robotic-assisted minimally invasive surgery (RMIS), new opportunities for objective and automated assessment frameworks have arisen. In this paper, we applied machine learning methods to automatically evaluate performance of the surgeon in RMIS. Six important movement features were used in the evaluation including completion time, path length, depth perception, speed, smoothness and curvature. ","authors_text":"Abhilash K. Pandya, Mahtab J. Fard, Michael D. Klein, Ratna B. Chinnam, R. Darin Ellis, Sattar Ameri","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2016-11-16T03:45:12Z","title":"Machine Learning Approach for Skill Evaluation in Robotic-Assisted Surgery"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1611.05136","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:e853a1ee487039c28df208e06524febd10d6c7033493bf0b00bacff6f77a956d","target":"record","created_at":"2026-05-18T00:57:45Z","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":"8c2762760ab354a267d53df6aa018a42387725ca26130afb48d5f3aed71e6012","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2016-11-16T03:45:12Z","title_canon_sha256":"6f701f2b6f0dbdcbfa0a37c8d2516d3c5d2061add4958227aa164cadfca6780a"},"schema_version":"1.0","source":{"id":"1611.05136","kind":"arxiv","version":1}},"canonical_sha256":"dec50c9c6db38555f95ad30fef2d1a6c8013c6d267505743b71c52c53b70533c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"dec50c9c6db38555f95ad30fef2d1a6c8013c6d267505743b71c52c53b70533c","first_computed_at":"2026-05-18T00:57:45.377963Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:57:45.377963Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5kXlZojqIAg//SnqT3h2Q9r9LBpVhdc7vd3KqHRMCaDOCIYX3c0bocGktYjJgVqOT+dKI5wWLEq5B9tJaih0Dg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:57:45.378621Z","signed_message":"canonical_sha256_bytes"},"source_id":"1611.05136","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e853a1ee487039c28df208e06524febd10d6c7033493bf0b00bacff6f77a956d","sha256:7eb77e3bcdf0e52836c5b9c85ad0cd5ba7fa96fef4f6b03c3ef6b23a29f1234b"],"state_sha256":"3684f55f86609a6672e2938fc99a284ebc9b1ac0403a71bdf9f1522d61d2bcc8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cLBuyThky1lfyi1/xpXPsvEFgwlYKPVaVMA0YgGMdSaT0k64s3mchAIB0x8fAoWoQ7P2AqL7UqLLzt7JMwPWCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-12T08:37:13.726683Z","bundle_sha256":"6fc51123bbcd5ae23e3ee5401445420c9ad726e462970b0073a91b9178028e9f"}}