← The evidence ledger
Evidence row 116141
Observed , by baseline/1.
- Kind
- listing
- About
- source_record x402_bazaar:https://market.datapackvibe.com/x402/assistant-sector-ml-return-reason-per-label
- Recorded
- Previous row
- None: the first of its kind about this subject
- Body SHA-256
- 17145b4a1eb201036a07a1de745d12bae94220b7e5df2b1b2d14be0a9c89484a
- Leaf
- 0x65ad184103b116388f0823fc89dc89175d5c09fbb562e20dad201b747f06f7a2
What was observed
{
"endpoints": [
[
"x402",
"https://market.datapackvibe.com/x402/assistant-sector-ml-return-reason-per-label"
]
],
"name": "market.datapackvibe.com/x402/assistant-sector-ml-return-reason-per-label",
"owner_address": "0x8bc2aecdd86097f74a1a5fa17764108d9a683c8c",
"raw": {
"accepts": [
{
"amount": "10000",
"asset": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
"extra": {
"name": "USD Coin",
"version": "2"
},
"maxTimeoutSeconds": 300,
"network": "eip155:8453",
"payTo": "0x8bc2AECdD86097F74a1a5fa17764108D9a683C8C",
"scheme": "exact"
}
],
"description": "Return reason - Per-label precision and recall: Per-label precision and recall for Return reason. Up to 200 supplied labelled text records. Local dataset tools, evaluation and small naive-Bayes baselines; no hosted model or foundation-model training. One of 25 profiles or calculations across 20 shared operations in this sector. 0.01 USDC includes one bounded per-label precision and recall deliverable.",
"extensions": {
"bazaar": {
"info": {
"input": {
"body": {
"records": [
{
"actual": "damaged",
"id": "example-0-0",
"predicted": "damaged",
"text": "damaged sample document number 0 for this supplied dataset."
},
{
"actual": "damaged",
"id": "example-0-1",
"predicted": "damaged",
"text": "damaged sample document number 1 for this supplied dataset."
},
{
"actual": "damaged",
"id": "example-0-2",
"predicted": "damaged",
"text": "damaged sample document number 2 for this supplied dataset."
},
{
"actual": "wrong_item",
"id": "example-1-0",
"predicted": "wrong_item",
"text": "wrong_item sample document number 0 for this supplied dataset."
},
{
"actual": "wrong_item",
"id": "example-1-1",
"predicted": "wrong_item",
"text": "wrong_item sample document number 1 for this supplied dataset."
},
{
"actual": "wrong_item",
"id": "example-1-2",
"predicted": "wrong_item",
"text": "wrong_item sample document number 2 for this supplied dataset."
},
{
"actual": "unwanted",
"id": "example-2-0",
"predicted": "unwanted",
"text": "unwanted sample document number 0 for this supplied dataset."
},
{
"actual": "unwanted",
"id": "example-2-1",
"predicted": "unwanted",
"text": "unwanted sample document number 1 for this supplied dataset."
},
{
"actual": "unwanted",
"id": "example-2-2",
"predicted": "unwanted",
"text": "unwanted sample document number 2 for this supplied dataset."
},
{
"actual": "other",
"id": "example-3-0",
"predicted": "other",
"text": "other sample document number 0 for this supplied dataset."
},
{
"actual": "other",
"id": "example-3-1",
"predicted": "other",
"text": "other sample document number 1 for this supplied dataset."
},
{
"actual": "other",
"id": "example-3-2",
"predicted": "other",
"text": "other sample document number 2 for this supplied dataset."
}
]
},
"bodyType": "json",
"method": "POST",
"type": "http"
},
"output": {
"example": {
"files": [],
"order_id": "ord_example",
"result": {
"completed": true,
"workflow": "sector-ml-return-reason-per-label"
},
"sku": "assistant-sector-ml-return-reason-per-label",
"status": "delivered"
},
"type": "json"
}
},
"schema": {
"$schema": "https://json-schema.org/draft/2020-12/schema",
"properties": {
"input": {
"additionalProperties": false,
"properties": {
"body": {
"additionalProperties": false,
"properties": {
"records": {
"default": [
{
"actual": "damaged",
"id": "example-0-0",
"predicted": "damaged",
"text": "damaged sample document number 0 for this supplied dataset."
},
{
"actual": "damaged",
"id": "example-0-1",
"predicted": "damaged",
"text": "damaged sample document number 1 for this supplied dataset."
},
{
"actual": "damaged",
"id": "example-0-2",
"predicted": "damaged",
"text": "damaged sample document number 2 for this supplied dataset."
},
{
"actual": "wrong_item",
"id": "example-1-0",
"predicted": "wrong_item",
"text": "wrong_item sample document number 0 for this supplied dataset."
},
{
"actual": "wrong_item",
"id": "example-1-1",
"predicted": "wrong_item",
"text": "wrong_item sample document number 1 for this supplied dataset."
},
{
"actual": "wrong_item",
"id": "example-1-2",
"predicted": "wrong_item",
"text": "wrong_item sample document number 2 for this supplied dataset."
},
{
"actual": "unwanted",
"id": "example-2-0",
"predicted": "unwanted",
"text": "unwanted sample document number 0 for this supplied dataset."
},
{
"actual": "unwanted",
"id": "example-2-1",
"predicted": "unwanted",
"text": "unwanted sample document number 1 for this supplied dataset."
},
{
"actual": "unwanted",
"id": "example-2-2",
"predicted": "unwanted",
"text": "unwanted sample document number 2 for this supplied dataset."
},
{
"actual": "other",
"id": "example-3-0",
"predicted": "other",
"text": "other sample document number 0 for this supplied dataset."
},
{
"actual": "other",
"id": "example-3-1",
"predicted": "other",
"text": "other sample document number 1 for this supplied dataset."
},
{
"actual": "other",
"id": "example-3-2",
"predicted": "other",
"text": "other sample document number 2 for this supplied dataset."
}
],
"items": {
"additionalProperties": false,
"properties": {
"actual": {
"enum": [
"damaged",
"wrong_item",
"unwanted",
"other"
],
"type": "string"
},
"id": {
"default": "",
"maxLength": 80,
"minLength": 1,
"type": "string"
},
"predicted": {
"enum": [
"damaged",
"wrong_item",
"unwanted",
"other"
],
"type": "string"
},
"text": {
"default": "",
"maxLength": 1000,
"type": "string"
}
},
"required": [
"id",
"text",
"actual",
"predicted"
],
"type": "object"
},
"maxItems": 200,
"minItems": 2,
"type": "array"
}
},
"required": [
"records"
],
"type": "object"
},
"bodyType": {
"enum": [
"json",
"form-data",
"text"
],
"type": "string"
},
"method": {
"enum": [
"POST"
],
"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"
}
}
},
"lastUpdated": "2026-10-24T12:10:31.864Z",
"quality": {
"l30DaysTotalCalls": 3,
"l30DaysUniquePayers": 1,
"lastCalledAt": "2026-10-24T12:10:29.646Z"
},
"resource": "https://market.datapackvibe.com/x402/assistant-sector-ml-return-reason-per-label",
"tags": [
"ai",
"sector-ml",
"workflow"
],
"type": "http",
"x402Version": 2
},
"source": "x402_bazaar",
"summary": "Return reason - Per-label precision and recall: Per-label precision and recall for Return reason. Up to 200 supplied labelled text records. Local dataset tools, evaluation and small naive-Bayes baselines; no hosted model or foundation-model training. One of 25 profiles or calculations across 20 shared operations in this sector. 0.01 USDC includes one bounded per-label precision and recall deliverable."
}What the leaf hashes
{"body":"17145b4a1eb201036a07a1de745d12bae94220b7e5df2b1b2d14be0a9c89484a","id":116141,"kind":"listing","method":"baseline/1","observed_us":1793025609219238,"prev":null,"subject":"x402_bazaar:https://market.datapackvibe.com/x402/assistant-sector-ml-return-reason-per-label","subject_kind":"source_record"}Proof
Fold these into the leaf in order, hashing each sorted pair with keccak256, to reach the root of (296695 rows).
- 0x65ad14bb8f5b79e9c0200895184ea604824709abaa670f80d551210b238911c2
- 0xcd51542f0fb6a07cf233935f0a567065a057c7b02d383f3d8199a747403f789a
- 0x5cb5d546709e375cd75953cc93f63474a95e53f1c43c55ca68d41116280ec8c9
- 0x5f0a182c17b632728cf65a695fe84c87c735c770055fe6db8f073ef674e7e779
- 0x566f8973ff6dc939a540dbdac505caa82c5bc6f934a6a9493500046b92e84e74
- 0x5c83ca3daad3ad949e5a71856f7c9ac6adc81f6504fb969481300adfea82836f
- 0xa4749000528ba50c89d84c808175aafce643a0760697b0362108bca6fde0f65f
- 0x2d3853d593e9d3722e1943818695c5ebbd034e5ecf8829fd8b084f77b9e350f5
- 0x61265e6f546630d1b2e8062415c704111501a1eb9cf68051cc6a4cdcc97f8f08
- 0x5296420e1acf9644fca56dfcfebe9911f7cbd593b603e3a280043d869ff6edc4
- 0x2184826674dda59cfc6d24bc12b2c70a5f4db29f874e67fded919c1410503d2e
- 0x611b1c1b68d04a71934006e383071a8f3836400d60beb86d81dd038bc102029f
- 0x13f4b94ecf613d585c952b5363dad2b247a55371eb8e358bb89dc033e83128b1
- 0x9a79c65e077cd9da9d436b3ade6f5ddc0d244510c4d5903ef2f02d81205f7666
- 0xa2d436d488e3600b0e5c3e3ed9c9234cd52853c59830b786334fd0c4292d9f40
- 0x47b89901b0f07938a6b9a66ddf35683903f79d756a7c7763665fd632758b08d0
- 0x9a83be955a206deb65b995adfd92c58fa31c95fbbf926bd199d300e70b08b26d
- 0x20704208aa6923d6b2450ef74ede87a6e0265d46447926038fe9506e9e154b2d
- 0x9b9ce5b74b9bab5121612ef6b64920a8d453cbf311096a423eef9702747e868a
- Day root
- 0xf43e8dcc3d451a4788b26be904c55e8c4c0fa75c9666796c51db38d37e2c0df8
- Chained
- 0x702d5ac508f08b0d1accf36af25822d8e5660367494edd17a642fb61e158a57a
- Published
- On Arc Testnet, block 69251483: 0x495162f8936e19f0039918feebe6c307f327cd6bf8c37219620b1970041fa9ae