← The evidence ledger
Evidence row 76547
Observed , by baseline/1.
- Kind
- listing
- About
- source_record x402_bazaar:https://hubvibe-io.com/work/stats/probability
- Recorded
- Previous row
- None: the first of its kind about this subject
- Body SHA-256
- 3f705358e411a6b86227ae2fa2225e546fa8cfb1e02eb7101ff5b07dea282442
- Leaf
- 0x6ba8da79b2f411cd286b8b3261f8cf2942dd1301285d0a09a55a3d9ddee6a905
What was observed
{
"endpoints": [
[
"x402",
"https://hubvibe-io.com/work/stats/probability"
]
],
"name": "HubVibe",
"owner_address": "0x837c40e2b4e976f43ffb4451ee281a00fa9477dd",
"raw": {
"accepts": [
{
"amount": "500000",
"asset": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
"extra": {
"name": "USD Coin",
"version": "2"
},
"maxTimeoutSeconds": 300,
"network": "eip155:8453",
"payTo": "0x837C40E2B4e976f43Ffb4451eE281A00fA9477dd",
"scheme": "exact"
},
{
"amount": "500000",
"asset": "EPjFWdd5AufqSSqeM2qN1xzybapC8G4wEGGkZwyTDt1v",
"extra": {
"feePayer": "BENrLoUbndxoNMUS5JXApGMtNykLjFXXixMtpDwDR9SP"
},
"maxTimeoutSeconds": 300,
"network": "solana:5eykt4UsFv8P8NJdTREpY1vzqKqZKvdp",
"payTo": "J1K4mdbvXEbJLRKpgxFcA7s66LWMCYHu71ye6Hz2icSh",
"scheme": "exact"
}
],
"description": "Predictive probability and regression engine: least-squares linear regression with standard errors, confidence and prediction intervals, a fitted normal distribution with quantiles and probability queries (P(y > t)), exact Student t and Jarque-Bera p-values. Points inline or from a BigQuery table. Deterministic arithmetic, no LLM: the same input always returns the same numbers. Input: points or table with x_column, y_column; optional metrics, predict_x, probability_queries.",
"extensions": {
"bazaar": {
"info": {
"input": {
"body": {
"points": [
[
1,
2.1
],
[
2,
3.9
],
[
3,
6.2
],
[
4,
7.8
],
[
5,
10.1
]
],
"predict_x": [
6
],
"probability_queries": [
{
"below": 8
}
]
},
"bodyType": "json",
"method": "POST",
"type": "http"
},
"output": {
"type": "json"
}
},
"schema": {
"$schema": "https://json-schema.org/draft/2020-12/schema",
"properties": {
"input": {
"additionalProperties": false,
"properties": {
"body": {
"additionalProperties": false,
"oneOf": [
{
"required": [
"points"
]
},
{
"required": [
"table",
"x_column",
"y_column"
]
}
],
"properties": {
"alpha": {
"exclusiveMaximum": 1,
"exclusiveMinimum": 0,
"type": "number"
},
"distribution_of": {
"enum": [
"y",
"x",
"residuals"
],
"type": "string"
},
"language": {
"maxLength": 35,
"pattern": "^[A-Za-z]{2,3}(-[A-Za-z0-9]{2,8})*$",
"type": "string"
},
"max_rows": {
"maximum": 100000,
"minimum": 3,
"type": "integer"
},
"metrics": {
"items": {
"enum": [
"linear_regression",
"normal_distribution",
"p_values",
"prediction"
],
"type": "string"
},
"minItems": 1,
"type": "array",
"uniqueItems": true
},
"points": {
"items": {
"oneOf": [
{
"items": {
"type": "number"
},
"maxItems": 2,
"minItems": 2,
"type": "array"
},
{
"additionalProperties": false,
"properties": {
"x": {
"type": "number"
},
"y": {
"type": "number"
}
},
"required": [
"x",
"y"
],
"type": "object"
}
]
},
"maxItems": 100000,
"minItems": 2,
"type": "array"
},
"predict_x": {
"items": {
"type": "number"
},
"maxItems": 100,
"minItems": 1,
"type": "array"
},
"probability_queries": {
"items": {
"additionalProperties": false,
"maxProperties": 1,
"minProperties": 1,
"properties": {
"above": {
"type": "number"
},
"below": {
"type": "number"
},
"between": {
"items": {
"type": "number"
},
"maxItems": 2,
"minItems": 2,
"type": "array"
}
},
"type": "object"
},
"maxItems": 50,
"type": "array"
},
"table": {
"type": "string"
},
"x_column": {
"type": "string"
},
"y_column": {
"type": "string"
}
},
"required": [],
"type": "object"
},
"bodyType": {
"enum": [
"json",
"form-data",
"text"
],
"type": "string"
},
"method": {
"enum": [
"POST",
"PUT",
"PATCH"
],
"type": "string"
},
"type": {
"const": "http",
"type": "string"
}
},
"required": [
"type",
"method",
"bodyType",
"body"
],
"type": "object"
},
"output": {
"properties": {
"example": {
"type": "object"
},
"type": {
"type": "string"
}
},
"required": [
"type"
],
"type": "object"
}
},
"required": [
"input"
],
"type": "object"
}
}
},
"iconUrl": "https://res.cloudinary.com/bdb-prod/image/upload/c_fill,ar_1:1,w_256,h_256,f_auto,q_auto/v1791248901/bazaar-icons/4e922acf935716fa.png",
"lastUpdated": "2026-10-19T06:35:25.494Z",
"quality": {
"l30DaysTotalCalls": 3,
"l30DaysUniquePayers": 1,
"lastCalledAt": "2026-10-19T06:35:26.192Z"
},
"resource": "https://hubvibe-io.com/work/stats/probability",
"serviceName": "HubVibe",
"tags": [
"statistics",
"regression",
"probability",
"prediction",
"confidence-interval"
],
"type": "http",
"x402Version": 2
},
"source": "x402_bazaar",
"summary": "Predictive probability and regression engine: least-squares linear regression with standard errors, confidence and prediction intervals, a fitted normal distribution with quantiles and probability queries (P(y > t)), exact Student t and Jarque-Bera p-values. Points inline or from a BigQuery table. Deterministic arithmetic, no LLM: the same input always returns the same numbers. Input: points or table with x_column, y_column; optional metrics, predict_x, probability_queries."
}What the leaf hashes
{"body":"3f705358e411a6b86227ae2fa2225e546fa8cfb1e02eb7101ff5b07dea282442","id":76547,"kind":"listing","method":"baseline/1","observed_us":1793025492425206,"prev":null,"subject":"x402_bazaar:https://hubvibe-io.com/work/stats/probability","subject_kind":"source_record"}Proof
Its day has not closed yet. A day closes ten minutes after midnight UTC; the proof appears here then.