{"_canonicalization":{"envelope_id":"axm_ + sha256(envelope minus {signature, axiom_id, anchors})","envelope_signature":"ed25519(envelope minus {signature, axiom_id})","json":"sort_keys=True, separators=(',',':'), ensure_ascii=False, allow_nan=False, utf-8","leaf_hash":"sha256(0x00 || canonical_json(envelope_full))","seal_signature":"ed25519(seal minus {signature, sig_algorithm})"},"axiom_id":"axm_e62a623426e38641ada65e3876574187b974b6357320ab620b2a737b153349ec","bitcoin_anchor":{"bitcoin_attestations":[],"calendar_attestations":[],"ots_url":"","stamped_at":"","status":"pending_next_stamp"},"envelope":{"anchors":[{"chain":"crovia.axiom_graph","height":0,"merkle_proof":"spider_court_dockets_v1","root_at_anchor":"spider_court_dockets_v1"}],"axiom_id":"axm_e62a623426e38641ada65e3876574187b974b6357320ab620b2a737b153349ec","axiom_type":"AX.OBS","body":{"axiom_subtype":"legal.court_dockets.v1","category":"legal","fingerprint":"48ea6896e5bca5a897f290cf5915a58100786c7fa1cbffd5b665ad9c9020bd82","published":"2026-05-22T00:00:00-04:00","receipt_hash":"48ea6896e5bca5a897f290cf5915a58100786c7fa1cbffd5b665ad9c9020bd82","schema":"spider.legal.court_dockets.v1","spider":"court_dockets","spider_record":{"axiom_subtype":"legal.court_dockets.v1","category":"legal","decision_hint":"POSITIVE","envelope_target":"AX.OBS","fingerprint":"48ea6896e5bca5a897f290cf5915a58100786c7fa1cbffd5b665ad9c9020bd82","observed_at":"2026-05-23T05:47:12.856536Z","parent_run_hash":"b0e39840cd59fe80f540a53b07247b7e9e402bb05e81b84d2228310deb2092cf","published":"2026-05-22T00:00:00-04:00","runtime_version":"0.1.0","schema":"spider.legal.court_dockets.v1","source_status":200,"source_url":"https://www.courtlistener.com/feed/search/?q=chatgpt&type=r&order_by=dateFiled+desc","spider":"court_dockets","summary_excerpt":"<p>Llama to generate derivative works, clones of their work, and mimicking their voices. 40. Meta needed books to develop “long context windows” — the ability to produce output based on long prompts — which was critical to competing with ChatGPT and other rivals. Internal documents confirm: “Anna’s Archive [a site of pirated material] is full of long context books that they will desperately need for llama4 to have long context.” 41. A large language model’s output is entirely</p><br>\n    \n    <a href=\"/docket/73384790/1/hobbs-v-platforms-inc/\">Original document</a>","title":"HOBBS v. PLATFORMS, INC.","url":"https://www.courtlistener.com/docket/73384790/1/hobbs-v-platforms-inc/","vendor":"court_dockets"},"summary":"<p>Llama to generate derivative works, clones of their work, and mimicking their voices. 40. Meta needed books to develop “long context windows” — the ability to produce output based on long prompts — which was critical to competing with ChatGPT and other rivals. Internal documents confirm: “Anna’s Archive [a site of pirated material] is full of long context books that they will desperately need for llama4 to have long context.” 41. A large language model’s output is entirely</p><br>\n    \n    <a href=\"/docket/73384790/1/hobbs-v-platforms-inc/\">Original document</a>","title":"HOBBS v. PLATFORMS, INC.","vendor":"court_dockets"},"confidence":{"method":"deterministic"},"decision":"POSITIVE","issued_at":"2026-05-23T05:47:12Z","notes":"Spider court_dockets (legal) legal.court_dockets.v1","object":{"captured_by":"crovia.spider.court_dockets","primary_source_url":"https://www.courtlistener.com/docket/73384790/1/hobbs-v-platforms-inc/"},"predecessors":[],"schema":"crovia.axiom.v1","signature":"ed25519:9aa9b02b841a30b109400e3c8f3977d08892d932913a12103c1fca43b611cb67ae0ddca476c1af18bd9645f5f6838b9d2acd893eeb98f349240e7eeda8f89102","signer":"crovia.substrate","subject":{"observed_at":"2026-05-23T05:47:12Z","source_collector":"spider:court_dockets","target_id":"https://www.courtlistener.com/docket/73384790/1/hobbs-v-platforms-inc/"},"tsa":{"authority":"crovia.substrate.bootstrap","rfc3161_token":"{\"kind\":\"crovia.bootstrap.tsa\",\"source_jsonl\":\"/opt/crovia/spider/data/legal/court_dockets_v1.jsonl\",\"source_seal_merkle_root\":\"spider_court_dockets_v1\",\"upgrade_path\":\"Sessione H \\u2014 OpenTimestamps weekly anchor\"}"},"zk_mode":"clear","zk_proof":null},"ledger":{"leaf_hash":"1628a1f90903c05907bc90c466f8786093670a17c2816a0e81d5c547e8285047","leaf_index":148100,"ledger_path":"/opt/crovia/substrate/axiom_ledger.jsonl"},"merkle_proof":{"hash_alg":"sha256","leaf_prefix":"0x00","node_prefix":"0x01","odd_leaf_rule":"duplicate_last","path":[{"sibling":"95b741ad8e8e439356de435f7bd2210bb077fe8773acd4ebaaec7854394ac2ff","side":"right"},{"sibling":"40201cd51346e378c46dfb78e80a2099bfff7a24a1bc0f861e7540bb13de5ae8","side":"right"},{"sibling":"096f497dd46a59157130bb2105b87577681987961387dfeaf74b6eb84168f611","side":"left"},{"sibling":"675e9892100f0b75a3981f6103c4ce96f665586844797c83996820694db2121f","side":"right"},{"sibling":"9f48178a7adec7d57189d2329fecff89292e13d53735be582cd5060b859a23c2","side":"right"},{"sibling":"68f7c9261540bfa85c4c6e1194400d472635c03f3573483263b07161a67ceb85","side":"right"},{"sibling":"7b84b9572ef31f052959edc4c36dca1cb76c6fe010107495a0b57345fea8a82e","side":"right"},{"sibling":"ce8423e7b33fd98ad2188ec515d860afebe3ce0e74717c41376c90ea6acfb384","side":"left"},{"sibling":"c5d582bc1cdd6d6494fd9e29c8b4aadd02d777f7ef92fc6d4afad7ee42785e79","side":"right"},{"sibling":"d337a9fdcfc121e9691d8db9173af6a3fe0c33d4a6d5f0c8a7a01af04f9fb856","side":"left"},{"sibling":"8b39e07457f5cc5d687d2ae42284dbe705bb87084e7db4b626aff81e51dacd19","side":"right"},{"sibling":"79a713e1e345ccb99c5fe994a11708c8e9bcfa2e91f940d70421cb7d8d77ecc6","side":"right"},{"sibling":"249870fb494bef050c409081e5de45f9042938d7b2823524ee496f296aa63667","side":"right"},{"sibling":"96c48ee8328f1b7925a4cc4421df5cb0bd81c92a5d8354c93126fa5f0166d225","side":"right"},{"sibling":"35ca36cee447f0ef7064a25d55f59357c66901e31427729c4c1d8b14aa8adb6c","side":"left"},{"sibling":"4e13b4a3e69bb83d13913477a782913ce03937edd65046853c1964d3cbb6564b","side":"right"},{"sibling":"0f7b2df1c4580bf7bb7c24b9158ba20593a06af18a5f18d0973e5eff20c35cd8","side":"right"},{"sibling":"d841ad93efda0869e5eb97678f348f03f5caab4353e05ff4bf18f47fb945b822","side":"left"}]},"schema":"crovia.axiom_proof.v1","seal":{"first_collector_run_id":"","first_receipt_hash":"","jsonl_path":"/opt/crovia/substrate/axiom_ledger.jsonl","key_id":"430895f101d38164","last_collector_run_id":"","last_receipt_hash":"","leaf_count":148601,"merkle_root":"44900cffd986f40535c83f46a250e86fbf1019d41f27080a00fbf9b8d77ec33a","public_key_hex":"cf742e26f75669dc673cb5c0786a1ae23ae8ca19c347317192ce40c28a7ff25c","run_id":"hourly_json_retrofit_20260524T133701Z","schema":"crovia.seal.v1","seal_family_version":"crovia-seal-family/1","seal_kind":"substrate_batch","sealed_at":"2026-05-24T13:37:32Z","sig_algorithm":"ed25519","signature":"059e428c3c5241de303721ad6ac7b748758372180f3f0a717810312aecd6fab073abb3ea264157666de581a2b361c4c6e2aa8ca081b08ce9be090721f0e3400e","signer_version":"1.1.0"},"trust_root":{"key_id":"430895f101d38164","public_key_hex":"cf742e26f75669dc673cb5c0786a1ae23ae8ca19c347317192ce40c28a7ff25c","signature_algorithm":"ed25519","url":"/registry/canon/TRUST_ROOT.md"},"verifier":{"spec":"/registry/canon/AXIOM_RECEIPT_v1.md","url":"/v/axm_e62a623426e38641ada65e3876574187b974b6357320ab620b2a737b153349ec"}}