{"_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_2b222b186a228920147b6e79ca6cc19a7a4b420eef3cc5850d76f4fea18c8f44","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_vendor_press_v1","root_at_anchor":"spider_vendor_press_v1"}],"axiom_id":"axm_2b222b186a228920147b6e79ca6cc19a7a4b420eef3cc5850d76f4fea18c8f44","axiom_type":"AX.OBS","body":{"axiom_subtype":"news.vendor_press.v1","category":"news","fingerprint":"e28703b814c140016dcf8432c946ac4b8184473e509635fd9d98022842e2aea3","published":"Thu, 02 Jul 2026 00:00:00 -0400","receipt_hash":"e28703b814c140016dcf8432c946ac4b8184473e509635fd9d98022842e2aea3","schema":"spider.news.vendor_press.v1","spider":"vendor_press","spider_record":{"axiom_subtype":"news.vendor_press.v1","category":"news","decision_hint":"POSITIVE","envelope_target":"AX.OBS","fingerprint":"e28703b814c140016dcf8432c946ac4b8184473e509635fd9d98022842e2aea3","observed_at":"2026-07-02T04:43:28.872255Z","parent_run_hash":"9f528c2a80e5b201c2a66ae885c05dd596ad2c3532bb4c6809c7c9704d10e650","published":"Thu, 02 Jul 2026 00:00:00 -0400","runtime_version":"0.1.0","schema":"spider.news.vendor_press.v1","source_status":200,"source_url":"https://export.arxiv.org/rss/cs.AI","spider":"vendor_press","summary_excerpt":"arXiv:2511.06701v3 Announce Type: replace-cross \nAbstract: AI-Scientist systems risk manufacturing spurious discoveries through uncontrolled multiple testing. We present a functional architecture that enforces statistical rigor at two levels: a Haskell embedded domain-specific language (the Research monad) that makes it impossible to test a hypothesis without updating the error budget, and a declarative scaffold, backed by an OS-level sandbox, that makes validation data physically absent from the environment in which LLM-generated code runs. We ground the design in a machine-checked Lean~4 formalization of LORD++ online false-discovery-rate (FDR) control: we derive its error budget and prove both marginal and full FDR control, then close the gap to the implementation by verifying the budget's wealth invariant over IEEE~754 arithmetic in SPARK/Ada. To our knowledge this is the first verified chain from theorem to floating-point implementation for an online FDR procedure. In simulation, ","title":"Structural Enforcement of Statistical Rigor in AI-Driven Discovery: A Functional Architecture","url":"https://arxiv.org/abs/2511.06701","vendor":"arxiv_cs_ai"},"summary":"arXiv:2511.06701v3 Announce Type: replace-cross \nAbstract: AI-Scientist systems risk manufacturing spurious discoveries through uncontrolled multiple testing. We present a functional architecture that enforces statistical rigor at two levels: a Haskell embedded domain-specific language (the Research monad) that makes it impossible to test a hypothesis without updating the error budget, and a declarative scaffold, backed by an OS-level sandbox, that makes validation data physically absent from the environment in which LLM-generated code runs. We ground the design in a machine-checked Lean~4 formalization of LORD++ online false-discovery-rate (FDR) control: we derive its error budget and prove both marginal and full FDR control, then close the gap to the implementation by verifying the budget's wealth invariant over IEEE~754 arithmetic in SPARK/Ada. To our knowledge this is the first verified chain from theorem to floating-point implementation for an online FDR procedure. In simulation, ","title":"Structural Enforcement of Statistical Rigor in AI-Driven Discovery: A Functional Architecture","vendor":"arxiv_cs_ai"},"confidence":{"method":"deterministic"},"decision":"POSITIVE","issued_at":"2026-07-02T04:43:28Z","notes":"Spider vendor_press (news) news.vendor_press.v1","object":{"captured_by":"crovia.spider.vendor_press","primary_source_url":"https://arxiv.org/abs/2511.06701"},"predecessors":[],"schema":"crovia.axiom.v1","signature":"ed25519:eb14237ef498dae5d9d5dc939ca82cda3ca730d5e8a35658c4f2a7fd076497660cbdbf6df72646274a4bd443a405ce0dd8695b8bfec97853d1f364c5e15a6a0a","signer":"crovia.substrate","subject":{"observed_at":"2026-07-02T04:43:28Z","source_collector":"spider:vendor_press","target_id":"https://arxiv.org/abs/2511.06701"},"tsa":{"authority":"crovia.substrate.bootstrap","rfc3161_token":"{\"kind\":\"crovia.bootstrap.tsa\",\"source_jsonl\":\"/opt/crovia/spider/data/news/vendor_press_v1.jsonl\",\"source_seal_merkle_root\":\"spider_vendor_press_v1\",\"upgrade_path\":\"Sessione H \\u2014 OpenTimestamps weekly anchor\"}"},"zk_mode":"clear","zk_proof":null},"ledger":{"leaf_hash":"9ebfde600712ffc7e15ead6fcd7b127689f473e75d76fa8fbcb8250bdb977e97","leaf_index":272145,"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":"182569950229f92c7630e3f892ecfdc3f1771b74437dcd8ee896def335f14585","side":"left"},{"sibling":"57f5db5091a38b6782a23aeb9b3219afaef09c2bc04d4d636676deba9e26245a","side":"right"},{"sibling":"7fcb614377bc6cab1b3acadad76e7fb559c0090a73fa08084ebecf9117029deb","side":"right"},{"sibling":"9e40261997ed2a465d2a5f7a4d39c9f7709a3c52eab249d9248b1f56e1d22c5c","side":"right"},{"sibling":"230641473e1060fab54b3261416e084c29f4c3ac71238ec07abac7dd44727231","side":"left"},{"sibling":"7a4e6051ee4ccafdc229a14d2ffcc4160414213994def7800db212689e11be64","side":"right"},{"sibling":"cc11812168388f349eda6e2835541b5d57a65c6cb4b16845c8021c9edc28b8a4","side":"right"},{"sibling":"a4da43fbd278ae938a2a1e0683cf220afa6b847d646277957f6bc405a8bbc4ed","side":"right"},{"sibling":"9c42dafc1ed28ef38396701a14a02d047efb8a9fb42065359d5d7f39d656a53b","side":"left"},{"sibling":"4cfdd7f7072619c015edc477162c2cf29c6f70370acb8dbddf1eb590876d82fe","side":"left"},{"sibling":"43990c9db8fcb3172d821965dfac69152981af4108b8dc87bd32f15c0e56f4cf","side":"left"},{"sibling":"15dbacc2e5845fe3bb835797bb7647ab6f091e79adadd39f40c636980716c622","side":"right"},{"sibling":"7ecc1d0d471643b88d886db58cb02a77af4d1495674760c3867834550b143757","side":"right"},{"sibling":"8a09562f6b247c1c3cd1fea36cb3b8f1cf5c575479dd514573856a380a964bf5","side":"left"},{"sibling":"7b681d50e7d0a7b8d2a749507aed58030072539a90fab18de4f698743685cc00","side":"right"},{"sibling":"9b262645232510ff15bb7325ab858256f2914f711d2726caeafd49f5ca0fb7a9","side":"right"},{"sibling":"5bd94446b5721b713c5e4dcf4624b9bc682657ab2784af927caae7b80c297d7d","side":"right"},{"sibling":"21ac0b7091fe1133859bcd17b4f8da2fe37a2489d472dad508305740b483221b","side":"right"},{"sibling":"1cecb7f447febd025aac272837c80de218aecc6485d2395a509b2a1f1b9c746e","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":272319,"merkle_root":"dd4fa4deb1f207e8a7756821b4f940f39e9f06a25e6fa8500a21dd403318a5a7","public_key_hex":"cf742e26f75669dc673cb5c0786a1ae23ae8ca19c347317192ce40c28a7ff25c","run_id":"hourly_json_retrofit_20260702T053701Z","schema":"crovia.seal.v1","seal_family_version":"crovia-seal-family/1","seal_kind":"substrate_batch","sealed_at":"2026-07-02T05:38:06Z","sig_algorithm":"ed25519","signature":"68eb2e3bbc0f593bea7b5c3c110c90b6f4fe4fd8277d8dee7c866ba0471c1a50684aa4539c8a493e6d9c9202d8c03f4d897a0df3477e9ecd5b0ff03eb1016f00","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_2b222b186a228920147b6e79ca6cc19a7a4b420eef3cc5850d76f4fea18c8f44"}}