{"uid":"cap_K3ZJpL18SKprYbgJaUijY","slug":"label-review-record-quality-audit-two-measure-correlation-a0231e11","name":"Label Review — Record Quality Audit + Two-Measure Correlation","description":"Label review — Record quality audit + Two-measure correlation: Record quality audit + Two-measure correlation for supplied label review records (reviewed_records, changed_labels). 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.","url":"https://market.datapackvibe.com/x402/assistant-ib26-analytics-12-015?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","reviewed_records","changed_labels"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"dataset_group":{"type":"string","default":"","maxLength":80},"changed_labels":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"reviewed_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","changed_labels":1,"reviewed_records":10},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","changed_labels":2,"reviewed_records":20},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","changed_labels":3,"reviewed_records":15},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","changed_labels":4,"reviewed_records":30}],"maxItems":200,"minItems":1}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_2b5uk8d56X6WQlmrt4Z6o","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Runs a record quality audit and two-measure correlation analysis on up to 200 label review rows (reviewed_records, changed_labels), returning two independent analytical reports.","exampleAgentPrompt":"Can you audit the quality of my label review data and compute the correlation between reviewed_records and changed_labels? I have 4 rows from October 2026 across two dataset groups — group-a and group-b — with row IDs row-1 through row-4, dates from 2026-10-01 to 2026-10-04, reviewed_records values of 10, 20, 15, and 30, and changed_labels of 1, 2, 3, and 4.","exampleUseCases":[{"title":"ML pipeline label quality check","prompt":"I have a week of label review logs from our annotation team — 50 rows across three dataset groups with daily reviewed_records and changed_labels counts. Can you run a record quality audit and tell me how correlated those two metrics are across the dataset?"},{"title":"Detecting mislabeling spikes in a dataset","prompt":"We suspect one of our dataset groups has unusually high label change rates compared to records reviewed. Can you audit these 120 label review rows and show me the correlation between reviewed_records and changed_labels so I can spot which groups are outliers?"},{"title":"Post-review QA report for data team","prompt":"Our data team just finished a label review sprint and I need a quality audit report plus a correlation analysis between how many records were reviewed vs how many labels got changed. I've got up to 200 rows with dates, group names, and both count fields — can you generate those two reports?"}],"resultDescription":"Returns two independent analytical reports: (1) a record quality audit identifying issues such as nulls, out-of-range values, and data consistency problems across the reviewed_records and changed_labels fields; and (2) a two-measure correlation report quantifying the statistical relationship between reviewed_records and changed_labels, potentially broken down by dataset_group or date. No external lookups or predictions are made — all analysis is performed locally on the supplied rows.","failureModes":["Input array exceeds 200 rows — request rejected","Missing required fields (row_id, reviewed_records, changed_labels) — validation error","Date field does not match YYYY-MM-DD pattern — schema validation failure","All changed_labels or reviewed_records values are null — correlation cannot be computed","Fewer than 2 data points provided — insufficient data for correlation analysis"],"whenToPreferThis":"Choose this endpoint when you need both a data quality audit and a correlation analysis on label review data in a single call at low cost ($0.01 USDC for both reports). It is purpose-built for ML/annotation pipelines tracking reviewed_records and changed_labels per group and date. Prefer it over general-purpose analytics tools when your dataset is under 200 rows and you want offline, deterministic local analysis without external API calls or predictions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:39:10.984Z","isFirstParty":false,"canonicalSlug":"label-review-record-quality-audit-two-measure-correlation-a0231e11"}