{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:5TF7OLCYCQOHRGU352EBW7YLND","short_pith_number":"pith:5TF7OLCY","schema_version":"1.0","canonical_sha256":"eccbf72c58141c789a9bee881b7f0b68d54c74c9685094b38eb6e73005746cb8","source":{"kind":"arxiv","id":"1801.02256","version":1},"attestation_state":"computed","paper":{"title":"Rapid de novo shape encoding: a challenge to connectionist modeling","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":[],"primary_cat":"q-bio.NC","authors_text":"Ernest Greene","submitted_at":"2018-01-07T21:47:29Z","abstract_excerpt":"Neural network (connectionist) models are designed to encode image features and provide the building blocks for object and shape recognition. These models generally call for: a) initial diffuse connections from one neuron population to another, and b) training to bring about a functional change in those connections so that one or more high-tier neurons will selectively respond to a specific shape stimulus. Advanced models provide for translation, size, and rotation invariance. The present discourse notes that recent work on human perceptual skills has demonstrated immediate encoding of unknown"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1801.02256","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"q-bio.NC","submitted_at":"2018-01-07T21:47:29Z","cross_cats_sorted":[],"title_canon_sha256":"e2c71feddb5d734fa7fc72911fe3cf3599118c1e45d48fd3cb77335e469d97e8","abstract_canon_sha256":"687af9c3cb8716a21a6519e478df9cda140c9ff423e38ae224906f549d25be28"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:26:32.297403Z","signature_b64":"vbcSZeBDz+2MxOWP4eB2bDn00Yu9Cwp5Env63Pe1G3KKddzaAP3zpgHvgLDZ/6x91WPurBbqNRk5P1FwHO7EDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"eccbf72c58141c789a9bee881b7f0b68d54c74c9685094b38eb6e73005746cb8","last_reissued_at":"2026-05-18T00:26:32.296628Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:26:32.296628Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Rapid de novo shape encoding: a challenge to connectionist modeling","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":[],"primary_cat":"q-bio.NC","authors_text":"Ernest Greene","submitted_at":"2018-01-07T21:47:29Z","abstract_excerpt":"Neural network (connectionist) models are designed to encode image features and provide the building blocks for object and shape recognition. These models generally call for: a) initial diffuse connections from one neuron population to another, and b) training to bring about a functional change in those connections so that one or more high-tier neurons will selectively respond to a specific shape stimulus. Advanced models provide for translation, size, and rotation invariance. The present discourse notes that recent work on human perceptual skills has demonstrated immediate encoding of unknown"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1801.02256","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1801.02256","created_at":"2026-05-18T00:26:32.296760+00:00"},{"alias_kind":"arxiv_version","alias_value":"1801.02256v1","created_at":"2026-05-18T00:26:32.296760+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1801.02256","created_at":"2026-05-18T00:26:32.296760+00:00"},{"alias_kind":"pith_short_12","alias_value":"5TF7OLCYCQOH","created_at":"2026-05-18T12:32:08.215937+00:00"},{"alias_kind":"pith_short_16","alias_value":"5TF7OLCYCQOHRGU3","created_at":"2026-05-18T12:32:08.215937+00:00"},{"alias_kind":"pith_short_8","alias_value":"5TF7OLCY","created_at":"2026-05-18T12:32:08.215937+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/5TF7OLCYCQOHRGU352EBW7YLND","json":"https://pith.science/pith/5TF7OLCYCQOHRGU352EBW7YLND.json","graph_json":"https://pith.science/api/pith-number/5TF7OLCYCQOHRGU352EBW7YLND/graph.json","events_json":"https://pith.science/api/pith-number/5TF7OLCYCQOHRGU352EBW7YLND/events.json","paper":"https://pith.science/paper/5TF7OLCY"},"agent_actions":{"view_html":"https://pith.science/pith/5TF7OLCYCQOHRGU352EBW7YLND","download_json":"https://pith.science/pith/5TF7OLCYCQOHRGU352EBW7YLND.json","view_paper":"https://pith.science/paper/5TF7OLCY","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1801.02256&json=true","fetch_graph":"https://pith.science/api/pith-number/5TF7OLCYCQOHRGU352EBW7YLND/graph.json","fetch_events":"https://pith.science/api/pith-number/5TF7OLCYCQOHRGU352EBW7YLND/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/5TF7OLCYCQOHRGU352EBW7YLND/action/timestamp_anchor","attest_storage":"https://pith.science/pith/5TF7OLCYCQOHRGU352EBW7YLND/action/storage_attestation","attest_author":"https://pith.science/pith/5TF7OLCYCQOHRGU352EBW7YLND/action/author_attestation","sign_citation":"https://pith.science/pith/5TF7OLCYCQOHRGU352EBW7YLND/action/citation_signature","submit_replication":"https://pith.science/pith/5TF7OLCYCQOHRGU352EBW7YLND/action/replication_record"}},"created_at":"2026-05-18T00:26:32.296760+00:00","updated_at":"2026-05-18T00:26:32.296760+00:00"}