{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:FCPLY54SRBRW75V26FVQGAVTBX","short_pith_number":"pith:FCPLY54S","canonical_record":{"source":{"id":"2008.02595","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"q-bio.NC","submitted_at":"2020-08-06T11:57:07Z","cross_cats_sorted":["cs.AI","cs.CV","stat.AP"],"title_canon_sha256":"aa0b500a262da3b2c2abe59fba408231e4015c0bfa52f7e6520a0a01e45c734d","abstract_canon_sha256":"6b70bb4603af1e30a85f831e69df39a166ca498ec4818ec2a48bbb32fc26a3b1"},"schema_version":"1.0"},"canonical_sha256":"289ebc779288636ff6baf16b0302b30dd3e26027f700ae0576cd7f2481f7afe9","source":{"kind":"arxiv","id":"2008.02595","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2008.02595","created_at":"2026-07-05T01:48:11Z"},{"alias_kind":"arxiv_version","alias_value":"2008.02595v2","created_at":"2026-07-05T01:48:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2008.02595","created_at":"2026-07-05T01:48:11Z"},{"alias_kind":"pith_short_12","alias_value":"FCPLY54SRBRW","created_at":"2026-07-05T01:48:11Z"},{"alias_kind":"pith_short_16","alias_value":"FCPLY54SRBRW75V2","created_at":"2026-07-05T01:48:11Z"},{"alias_kind":"pith_short_8","alias_value":"FCPLY54S","created_at":"2026-07-05T01:48:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:FCPLY54SRBRW75V26FVQGAVTBX","target":"record","payload":{"canonical_record":{"source":{"id":"2008.02595","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"q-bio.NC","submitted_at":"2020-08-06T11:57:07Z","cross_cats_sorted":["cs.AI","cs.CV","stat.AP"],"title_canon_sha256":"aa0b500a262da3b2c2abe59fba408231e4015c0bfa52f7e6520a0a01e45c734d","abstract_canon_sha256":"6b70bb4603af1e30a85f831e69df39a166ca498ec4818ec2a48bbb32fc26a3b1"},"schema_version":"1.0"},"canonical_sha256":"289ebc779288636ff6baf16b0302b30dd3e26027f700ae0576cd7f2481f7afe9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:48:11.843662Z","signature_b64":"aSMnOOhxN68En7Lb1N8zKLpcc9Xs+h1c9vuX3RCS6gsMzh1ZQH7gE3t6lr+XeK/eso5B+SnlrZvsv7klCHLhCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"289ebc779288636ff6baf16b0302b30dd3e26027f700ae0576cd7f2481f7afe9","last_reissued_at":"2026-07-05T01:48:11.843229Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:48:11.843229Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2008.02595","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T01:48:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zAmi4friXlvlGmrcjLQCQUWddqKvCsdKDfiYe4sVJq0tOGDuD/APnb3QCh5rzmO5uUD4n7fvwLhh+Zh5MdNNDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T12:08:09.846318Z"},"content_sha256":"7a5b309c6e7d170889bbabba5a639b7d14d204484cf892164d1001425e260b0b","schema_version":"1.0","event_id":"sha256:7a5b309c6e7d170889bbabba5a639b7d14d204484cf892164d1001425e260b0b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:FCPLY54SRBRW75V26FVQGAVTBX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Gibbs Sampling with People","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CV","stat.AP"],"primary_cat":"q-bio.NC","authors_text":"Federico Adolfi, Manuel Anglada-Tort, Nori Jacoby, Ofer Tchernichovski, Pauline Larrouy-Maestri, Peter M. C. Harrison, Pol van Rijn, Raja Marjieh","submitted_at":"2020-08-06T11:57:07Z","abstract_excerpt":"A core problem in cognitive science and machine learning is to understand how humans derive semantic representations from perceptual objects, such as color from an apple, pleasantness from a musical chord, or seriousness from a face. Markov Chain Monte Carlo with People (MCMCP) is a prominent method for studying such representations, in which participants are presented with binary choice trials constructed such that the decisions follow a Markov Chain Monte Carlo acceptance rule. However, while MCMCP has strong asymptotic properties, its binary choice paradigm generates relatively little infor"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2008.02595","kind":"arxiv","version":2},"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/2008.02595/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":"2026-07-05T01:48:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jxidLNSIxhjVe5S1b6k7ehFk2z9EmzyF9Cqt43HfQz/pwhtmMrpTZfZbIa8tPq96pAyOVkGVsREVVcizk462AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T12:08:09.847205Z"},"content_sha256":"2e16c30825a101c0de58a00ca161ba33fb7364c787238d762d4b8225c79dd21d","schema_version":"1.0","event_id":"sha256:2e16c30825a101c0de58a00ca161ba33fb7364c787238d762d4b8225c79dd21d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FCPLY54SRBRW75V26FVQGAVTBX/bundle.json","state_url":"https://pith.science/pith/FCPLY54SRBRW75V26FVQGAVTBX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FCPLY54SRBRW75V26FVQGAVTBX/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":"2026-08-04T12:08:09Z","links":{"resolver":"https://pith.science/pith/FCPLY54SRBRW75V26FVQGAVTBX","bundle":"https://pith.science/pith/FCPLY54SRBRW75V26FVQGAVTBX/bundle.json","state":"https://pith.science/pith/FCPLY54SRBRW75V26FVQGAVTBX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FCPLY54SRBRW75V26FVQGAVTBX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:FCPLY54SRBRW75V26FVQGAVTBX","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":"6b70bb4603af1e30a85f831e69df39a166ca498ec4818ec2a48bbb32fc26a3b1","cross_cats_sorted":["cs.AI","cs.CV","stat.AP"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"q-bio.NC","submitted_at":"2020-08-06T11:57:07Z","title_canon_sha256":"aa0b500a262da3b2c2abe59fba408231e4015c0bfa52f7e6520a0a01e45c734d"},"schema_version":"1.0","source":{"id":"2008.02595","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2008.02595","created_at":"2026-07-05T01:48:11Z"},{"alias_kind":"arxiv_version","alias_value":"2008.02595v2","created_at":"2026-07-05T01:48:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2008.02595","created_at":"2026-07-05T01:48:11Z"},{"alias_kind":"pith_short_12","alias_value":"FCPLY54SRBRW","created_at":"2026-07-05T01:48:11Z"},{"alias_kind":"pith_short_16","alias_value":"FCPLY54SRBRW75V2","created_at":"2026-07-05T01:48:11Z"},{"alias_kind":"pith_short_8","alias_value":"FCPLY54S","created_at":"2026-07-05T01:48:11Z"}],"graph_snapshots":[{"event_id":"sha256:2e16c30825a101c0de58a00ca161ba33fb7364c787238d762d4b8225c79dd21d","target":"graph","created_at":"2026-07-05T01:48:11Z","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/2008.02595/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"A core problem in cognitive science and machine learning is to understand how humans derive semantic representations from perceptual objects, such as color from an apple, pleasantness from a musical chord, or seriousness from a face. Markov Chain Monte Carlo with People (MCMCP) is a prominent method for studying such representations, in which participants are presented with binary choice trials constructed such that the decisions follow a Markov Chain Monte Carlo acceptance rule. However, while MCMCP has strong asymptotic properties, its binary choice paradigm generates relatively little infor","authors_text":"Federico Adolfi, Manuel Anglada-Tort, Nori Jacoby, Ofer Tchernichovski, Pauline Larrouy-Maestri, Peter M. C. Harrison, Pol van Rijn, Raja Marjieh","cross_cats":["cs.AI","cs.CV","stat.AP"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"q-bio.NC","submitted_at":"2020-08-06T11:57:07Z","title":"Gibbs Sampling with People"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2008.02595","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":"sha256:7a5b309c6e7d170889bbabba5a639b7d14d204484cf892164d1001425e260b0b","target":"record","created_at":"2026-07-05T01:48:11Z","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":"6b70bb4603af1e30a85f831e69df39a166ca498ec4818ec2a48bbb32fc26a3b1","cross_cats_sorted":["cs.AI","cs.CV","stat.AP"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"q-bio.NC","submitted_at":"2020-08-06T11:57:07Z","title_canon_sha256":"aa0b500a262da3b2c2abe59fba408231e4015c0bfa52f7e6520a0a01e45c734d"},"schema_version":"1.0","source":{"id":"2008.02595","kind":"arxiv","version":2}},"canonical_sha256":"289ebc779288636ff6baf16b0302b30dd3e26027f700ae0576cd7f2481f7afe9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"289ebc779288636ff6baf16b0302b30dd3e26027f700ae0576cd7f2481f7afe9","first_computed_at":"2026-07-05T01:48:11.843229Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:48:11.843229Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"aSMnOOhxN68En7Lb1N8zKLpcc9Xs+h1c9vuX3RCS6gsMzh1ZQH7gE3t6lr+XeK/eso5B+SnlrZvsv7klCHLhCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T01:48:11.843662Z","signed_message":"canonical_sha256_bytes"},"source_id":"2008.02595","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7a5b309c6e7d170889bbabba5a639b7d14d204484cf892164d1001425e260b0b","sha256:2e16c30825a101c0de58a00ca161ba33fb7364c787238d762d4b8225c79dd21d"],"state_sha256":"c680626ef3e822557bd11a78e7e39231f247741f99af885abda6c6da19174ee4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yyWgAGTTt6J5TVp8g4BXmDaSsI/KcntTfdw84fBh8J0lf9coRyp914sl1bbTQN91RMm8Gcmv0wxjYMx5BFSVDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T12:08:09.853278Z","bundle_sha256":"073436629f0f38493f4612484b1f19f7f94d68bd6db5923b3972ef0d12bd41b2"}}