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score-geometric

station__noncompensatory__score-geometric external (needs EXECUTION_BACKEND_URL) noncompensatory non-pv Constructa Configa

Compute non-compensatory risk score using weighted geometric mean. Default Bayesian-heavy weights [PRR=0.15, ROR=0.15, IC025=0.35, EBGM05=0.35] maximize signal-to-noise discrimination (validated via 40-scenario simulation). A near-zero dimension collapses the composite.

Taxonomy

Linnaean classification joined from the algovigilance taxonomy index via the parent config's rank.

Rank	Value
domain	`Substrata`
kingdom	`Constructa`
phylum	`Configa`
class	`station-config`
order	`noncompensatory`
family	`mcp-tool-config`

Characteristics:

substrate: config
domain: pv
lifecycle: continuous
authority: read
compounding: producer
io: agent-request → tool-response

Input schema

drug stringrequired — Drug name
event stringrequired — Adverse event
prr numberrequired — Proportional Reporting Ratio
ror_lower numberrequired — ROR lower 95% confidence interval
ic025 numberrequired — Information Component 2.5th percentile
eb05 numberrequired — EBGM 5th percentile
n integerrequired — Number of cases
weights string — Custom weights as comma-separated: PRR,ROR,IC025,EBGM05 (must sum to 1.0). Default: 0.15,0.15,0.35,0.35

Example call

POST /api/mcp
Content-Type: application/json

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "station__noncompensatory__score-geometric",
    "arguments": {
      "drug": "",
      "event": "",
      "prr": 0,
      "ror_lower": 0,
      "ic025": 0,
      "eb05": 0,
      "n": 0
    }
  }
}

How to invoke from a client

From any MCP-aware client, add https://algovigilance.com/api/mcp as an MCP server, then call this tool by name. From a raw HTTP client, send the JSON-RPC body above to /api/mcp.

Agent-friendly formats

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