Evidence row 222130

What was observed

{
  "count": 15,
  "tools": [
    {
      "description": "Fetch a single blog post by slug, including the full article content.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "additionalProperties": false,
        "properties": {
          "slug": {
            "description": "Blog post slug, e.g. \"immunotherapy-breakthroughs\".",
            "type": "string"
          }
        },
        "required": [
          "slug"
        ],
        "type": "object"
      },
      "name": "get_blog_post"
    },
    {
      "description": "Fetch a single clinical trial by NCT id (or internal id), including eligibility criteria and locations.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "additionalProperties": false,
        "properties": {
          "nctId": {
            "description": "NCT id or internal id, e.g. \"NCT01234567\".",
            "type": "string"
          }
        },
        "required": [
          "nctId"
        ],
        "type": "object"
      },
      "name": "get_clinical_trial"
    },
    {
      "description": "Fetch a single research paper by its internal id or PubMed id.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "additionalProperties": false,
        "properties": {
          "idOrPubmedId": {
            "description": "Internal id or PubMed id, e.g. \"38123456\".",
            "type": "string"
          }
        },
        "required": [
          "idOrPubmedId"
        ],
        "type": "object"
      },
      "name": "get_research_paper"
    },
    {
      "description": "List editorial blog articles (excerpts). Use get_blog_post for full content. Filter by category, cancer-type tag, or keyword.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "additionalProperties": false,
        "properties": {
          "cancerType": {
            "description": "Filter by cancer-type tag.",
            "type": "string"
          },
          "category": {
            "description": "Filter by primary category.",
            "type": "string"
          },
          "limit": {
            "description": "Results per page (1–100, default 20).",
            "maximum": 100,
            "minimum": 1,
            "type": "integer"
          },
          "offset": {
            "description": "Number of results to skip (default 0).",
            "minimum": 0,
            "type": "integer"
          },
          "search": {
            "description": "Keyword search across title, excerpt, and content.",
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "list_blog_posts"
    },
    {
      "description": "List clinical trials from public registries (conditions, status, intervention type). Filter by condition, status (e.g. RECRUITING), or keyword.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "additionalProperties": false,
        "properties": {
          "condition": {
            "description": "Filter by condition.",
            "type": "string"
          },
          "limit": {
            "description": "Results per page (1–100, default 20).",
            "maximum": 100,
            "minimum": 1,
            "type": "integer"
          },
          "offset": {
            "description": "Number of results to skip (default 0).",
            "minimum": 0,
            "type": "integer"
          },
          "search": {
            "description": "Keyword search across title and description.",
            "type": "string"
          },
          "status": {
            "description": "Filter by trial status, e.g. RECRUITING.",
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "list_clinical_trials"
    },
    {
      "description": "List the pharmaceutical-compound characteristics (each scored on the −4…+4 scale) that can be used as preference keys in search_compounds.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {},
        "type": "object"
      },
      "name": "list_compound_characteristics"
    },
    {
      "description": "List FDA-approved oncology drugs with indication, company, approval date, and label links. Filter by cancer type, keyword, or approval date.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "additionalProperties": false,
        "properties": {
          "cancerType": {
            "description": "Filter by cancer type, e.g. lung, breast, prostate, colorectal, melanoma, leukemia, lymphoma.",
            "type": "string"
          },
          "from": {
            "description": "ISO date lower bound (e.g. 2024-01-01).",
            "type": "string"
          },
          "limit": {
            "description": "Results per page (1–100, default 20).",
            "maximum": 100,
            "minimum": 1,
            "type": "integer"
          },
          "offset": {
            "description": "Number of results to skip (default 0).",
            "minimum": 0,
            "type": "integer"
          },
          "search": {
            "description": "Keyword search across drug name, generic name, and indication.",
            "type": "string"
          },
          "to": {
            "description": "ISO date upper bound (e.g. 2024-12-31).",
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "list_fda_approvals"
    },
    {
      "description": "List curated cancer news articles aggregated from trusted sources. Filter by cancer type, keyword, or published date.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "additionalProperties": false,
        "properties": {
          "cancerType": {
            "description": "Filter by cancer type, e.g. lung, breast, prostate, colorectal, melanoma, leukemia, lymphoma.",
            "type": "string"
          },
          "from": {
            "description": "ISO date lower bound (e.g. 2024-01-01).",
            "type": "string"
          },
          "limit": {
            "description": "Results per page (1–100, default 20).",
            "maximum": 100,
            "minimum": 1,
            "type": "integer"
          },
          "offset": {
            "description": "Number of results to skip (default 0).",
            "minimum": 0,
            "type": "integer"
          },
          "search": {
            "description": "Keyword search across title, summary, and content.",
            "type": "string"
          },
          "to": {
            "description": "ISO date upper bound (e.g. 2024-12-31).",
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "list_news"
    },
    {
      "description": "List peer-reviewed oncology research papers ingested from PubMed (abstracts, authors, journal, plain-language summaries). Filter by cancer type, treatment type, keyword, or publication date.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "additionalProperties": false,
        "properties": {
          "cancerType": {
            "description": "Filter by cancer type, e.g. lung, breast, prostate, colorectal, melanoma, leukemia, lymphoma.",
            "type": "string"
          },
          "from": {
            "description": "ISO date lower bound (e.g. 2024-01-01).",
            "type": "string"
          },
          "limit": {
            "description": "Results per page (1–100, default 20).",
            "maximum": 100,
            "minimum": 1,
            "type": "integer"
          },
          "offset": {
            "description": "Number of results to skip (default 0).",
            "minimum": 0,
            "type": "integer"
          },
          "search": {
            "description": "Keyword search across title and abstract.",
            "type": "string"
          },
          "to": {
            "description": "ISO date upper bound (e.g. 2024-12-31).",
            "type": "string"
          },
          "treatmentType": {
            "description": "Filter by treatment type.",
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "list_research"
    },
    {
      "description": "Check whether the IBM MAMMAL prediction model is loaded and ready. No API key required. Call this before predict_* tools if a prior prediction timed out.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {},
        "type": "object"
      },
      "name": "mammal_health"
    },
    {
      "description": "Predict clinical-trial toxicity for a compound using IBM MAMMAL. Returns pred 1 (toxic / likely to fail trials) or 0 (not toxic) plus a raw score. Inference is CPU-bound and may take up to ~60s.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "additionalProperties": false,
        "properties": {
          "smiles": {
            "description": "Compound structure in SMILES notation.",
            "type": "string"
          }
        },
        "required": [
          "smiles"
        ],
        "type": "object"
      },
      "name": "predict_clintox"
    },
    {
      "description": "Predict drug–target binding affinity as pKd (−log10 Kd; higher = stronger binding) using IBM MAMMAL. Inference is CPU-bound and may take up to ~60s.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "additionalProperties": false,
        "properties": {
          "drug_seq": {
            "description": "Drug structure in SMILES notation.",
            "type": "string"
          },
          "norm_y_mean": {
            "description": "Optional normalization mean override.",
            "type": "number"
          },
          "norm_y_std": {
            "description": "Optional normalization standard-deviation override.",
            "type": "number"
          },
          "target_seq": {
            "description": "Target protein amino-acid sequence (single-letter codes).",
            "type": "string"
          }
        },
        "required": [
          "target_seq",
          "drug_seq"
        ],
        "type": "object"
      },
      "name": "predict_dti"
    },
    {
      "description": "Predict the binding-affinity class for a pair of proteins using the IBM MAMMAL biomedical foundation model. Returns label \"1\" (interacting) or \"0\" (non-interacting). Inference is CPU-bound and may take up to ~60s.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "additionalProperties": false,
        "properties": {
          "protein_a": {
            "description": "Amino-acid sequence, single-letter codes (ACDEFGHIKLMNPQRSTVWY), no FASTA header.",
            "type": "string"
          },
          "protein_b": {
            "description": "Amino-acid sequence, single-letter codes.",
            "type": "string"
          }
        },
        "required": [
          "protein_a",
          "protein_b"
        ],
        "type": "object"
      },
      "name": "predict_ppi"
    },
    {
      "description": "Find pharmaceutical compounds two ways: by example drugs you already know (fuzzy-matched), or by setting target characteristics on a −4…+4 scale. Provide exactly one of `examples` or `preferences`. Use list_compound_characteristics for the available preference names.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "additionalProperties": false,
        "properties": {
          "examples": {
            "description": "Known drug names to find similar compounds for, e.g. [\"aspirin\",\"ibuprofen\"]. Mutually exclusive with preferences.",
            "items": {
              "type": "string"
            },
            "type": "array"
          },
          "include_characteristics": {
            "description": "Include each result’s characteristic scores in the response.",
            "type": "boolean"
          },
          "limit": {
            "description": "Max results (1–100, default 20).",
            "maximum": 100,
            "minimum": 1,
            "type": "integer"
          },
          "preferences": {
            "additionalProperties": {
              "maximum": 4,
              "minimum": -4,
              "type": "number"
            },
            "description": "Map of characteristic name to desired value on the −4…+4 scale, e.g. {\"Neuroactive\":3,\"Immunoactive\":-2}. Omit a characteristic to ignore it. Mutually exclusive with examples.",
            "type": "object"
          }
        },
        "type": "object"
      },
      "name": "search_compounds"
    },
    {
      "description": "Search a keyword across every Cure Cancer With AI dataset at once — research papers, news, blog posts, FDA approvals, and clinical trials — with results grouped by type. Use this first for broad discovery, then fetch a single record by id/slug/nctId for full detail.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "additionalProperties": false,
        "properties": {
          "cancerType": {
            "description": "Filter by cancer type, e.g. lung, breast, prostate, colorectal, melanoma, leukemia, lymphoma.",
            "type": "string"
          },
          "limit": {
            "description": "Max results per dataset (1–100, default 5).",
            "maximum": 100,
            "minimum": 1,
            "type": "integer"
          },
          "q": {
            "description": "The keyword to search for, e.g. \"osimertinib\".",
            "type": "string"
          },
          "types": {
            "description": "Optional comma-separated datasets to narrow to: research,news,blog,fdaApprovals,clinicalTrials.",
            "type": "string"
          }
        },
        "required": [
          "q"
        ],
        "type": "object"
      },
      "name": "search_oncology"
    }
  ]
}

What the leaf hashes

{"body":"5f233cfc8353e1ca2437ac634a603e4a4dfc1ff16da53077cf93c5d0a6c7e40d","id":222130,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1793027827251510,"prev":null,"subject":"ec830a60-c4b6-4c81-8911-5b17f5d4aa35","subject_kind":"endpoint"}

Proof

Fold these into the leaf in order, hashing each sorted pair with keccak256, to reach the root of 2026-10-26 (296695 rows).

1. 0x63fae5db92f69bac338981c5c42f3c572a44b1666dced14185011342c974db69
2. 0x25828c50a71b16f323a30a656d65fe9c3e469a8692da8feb870a0403af2bde39
3. 0x913a71a8069bc833cfc3e96723d96292eaa14fb6db5a5367538a07594baeacb4
4. 0x6a70934b646ba40f2334858e040d9c46285db09e6fcf4e80104e3cd1d282adc3
5. 0x31f222d4ead7b4196a127cddc22a25d829cdc756c490861d33102ba582e455a3
6. 0x1e2ed519560e296d9905d8e3e7f1009ae9cc454dfa1afca2295a0f37044b5a36
7. 0x7454031409d767d32375d94f4a7ccdd0dba91df4e2789bb72e8fe869a5e299ef
8. 0x4795af00a7bbb1ecd25b1c765c32f7beffb65f1b7f27a30130dfe9ca142010f9
9. 0xaee65ca4355c3e6c6da6121ba2239ff3173fe956bc7a177c4570bd6029c7f47a
10. 0x0cf27acff17ee4b19c37230254fb064d664b48a3282643e35a74b6998aa0446b
11. 0xde5ff34fc9e6ff297fede5d3c4b4de6828c65b98246109399106064f912afa82
12. 0x3c8355143bb13802401d5a80f8a70809a59f429bc298f4912731fc8d207e4f43
13. 0x13f4b94ecf613d585c952b5363dad2b247a55371eb8e358bb89dc033e83128b1
14. 0x9a79c65e077cd9da9d436b3ade6f5ddc0d244510c4d5903ef2f02d81205f7666
15. 0xa2d436d488e3600b0e5c3e3ed9c9234cd52853c59830b786334fd0c4292d9f40
16. 0x47b89901b0f07938a6b9a66ddf35683903f79d756a7c7763665fd632758b08d0
17. 0x9a83be955a206deb65b995adfd92c58fa31c95fbbf926bd199d300e70b08b26d
18. 0x20704208aa6923d6b2450ef74ede87a6e0265d46447926038fe9506e9e154b2d
19. 0x9b9ce5b74b9bab5121612ef6b64920a8d453cbf311096a423eef9702747e868a

Day root

0xf43e8dcc3d451a4788b26be904c55e8c4c0fa75c9666796c51db38d37e2c0df8

Chained

0x702d5ac508f08b0d1accf36af25822d8e5660367494edd17a642fb61e158a57a

Published

On Arc Testnet, block 69251483: 0x495162f8936e19f0039918feebe6c307f327cd6bf8c37219620b1970041fa9ae