# Correction Logs — Adjacent Row Changes + Secondary-Measure Weighted Mean

> Correction Logs — Adjacent Row Changes + Secondary-Measure Weighted Mean is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-23).

Computes adjacent row changes and a secondary-measure weighted mean for up to 200 correction log records, returning two analytical reports in a single call.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-news-04-159?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-23
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/correction-logs-adjacent-row-changes-secondary-measure-weighted-mean-60f2cbb5
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_-H6uJnH4CHSlrosNQT2wX

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability correction-logs-adjacent-row-changes-secondary-measure-weighted-mean-60f2cbb5 -d '<json body>'
```

Example prompt: I have 4 rows of correction log data for my news channels — can you run both the adjacent row changes and the secondary-measure weighted mean analysis on correction_count, using these records: row-1 on 2026-10-01 for group-a with correction_count 10 and published_items 1, row-2 on 2026-10-02 for group-b with correction_count 20 and published_items 2, row-3 on 2026-10-03 for group-a with correction_count 15 and published_items 3, row-4 on 2026-10-04 for group-b with correction_count 30 and published_items 4?

## When to prefer this

Choose this endpoint when you have tabular correction log data (up to 200 rows) with correction_count and published_items fields and need both row-over-row delta analysis and a weighted mean in a single inexpensive call. It is best suited for editorial quality monitoring, news correction auditing, or publishing analytics pipelines where offline batch computation on supplied data is sufficient and no live data lookup or prediction is required.

## Known failure modes

- Empty or missing rows array returns an error
- More than 200 rows submitted exceeds the maxItems limit
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- row_id missing or empty string triggers required-field validation error
- field enum value outside 'correction_count' or 'published_items' is rejected
- Null values in both correction_count and published_items may produce undefined weighted mean
- Submitting non-numeric values for numeric fields causes type validation failure

## How this service works

Correction logs — Adjacent row changes + Secondary-measure weighted mean: Adjacent row changes + Secondary-measure weighted mean for supplied correction logs records (correction_count, published_items). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.

## Output

Returns two analytical reports: (1) adjacent row changes showing how correction_count or published_items values shift between consecutive rows, and (2) a weighted mean of the selected primary field using the secondary measure as weights — both computed locally against the supplied data, with no external lookups or predictions.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "channel_group",
     "date",
     "correction_count",
     "published_items"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "channel_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "published_items": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "correction_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "channel_group": "group-a",
     "published_items": 1,
     "correction_count": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "channel_group": "group-b",
     "published_items": 2,
     "correction_count": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "channel_group": "group-a",
     "published_items": 3,
     "correction_count": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "channel_group": "group-b",
     "published_items": 4,
     "correction_count": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "correction_count",
    "published_items"
   ],
   "type": "string",
   "default": "correction_count"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/correction-logs-adjacent-row-changes-secondary-measure-weighted-mean-60f2cbb5/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from market.datapackvibe.com](https://www.zero.xyz/host/market.datapackvibe.com/llms.txt)