{"uid":"cap_oSPzM02-Y3tX10D6OWi7T","slug":"label-review-analytics-iqr-outlier-flags-secondary-measure-weighted-123fdfb1","name":"Label Review Analytics: IQR Outlier Flags + Secondary-Measure Weighted Mean","description":"Label review — IQR outlier flags + Secondary-measure weighted mean: IQR outlier flags + Secondary-measure weighted mean 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-12-177?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},"field":{"enum":["reviewed_records","changed_labels"],"type":"string","default":"reviewed_records"}}},"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_9giPCCYLEcCZqku-jh4TS","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 two local analytical reports on label review data: IQR-based outlier detection on a chosen field and a secondary-measure weighted mean, for up to 200 rows.","exampleAgentPrompt":"Run IQR outlier flagging and a weighted mean analysis on my label review records — I have up to 50 rows with reviewed_records and changed_labels per dataset group, and I want to analyze the reviewed_records field.","exampleUseCases":[{"title":"Annotation quality audit by group","prompt":"I have 80 label review records across several dataset groups with dates, reviewed_records counts, and changed_labels counts. Can you flag any IQR outliers and compute the weighted mean for reviewed_records so I can spot inconsistent annotators?"},{"title":"Changed labels anomaly detection","prompt":"Run the IQR outlier detection and weighted mean reports on my changed_labels data — I've got about 120 rows of daily label review logs across two groups and I want to know which days had abnormally high label changes."},{"title":"Pre-release dataset review sanity check","prompt":"Before we ship this dataset, can you analyze my 30 label review rows for the changed_labels field — flag any outliers using IQR and give me a weighted mean so I can confirm the labeling was consistent?"}],"resultDescription":"Returns two independent analytical reports: (1) IQR outlier flags indicating which rows fall outside the interquartile range for the selected field, and (2) a secondary-measure weighted mean computed across the supplied rows. Both reports are derived entirely from the submitted data with no external lookups.","failureModes":["Fewer than 1 row submitted — returns validation error","More than 200 rows submitted — request rejected due to row limit","Invalid date format (non-YYYY-MM-DD) — schema validation failure","Null or missing required fields (row_id, reviewed_records, changed_labels) — error response","Invalid field enum value — rejected at schema level","Numeric values outside allowed range — schema rejection"],"whenToPreferThis":"Choose this endpoint when you need fast, local statistical quality checks on label review data — specifically IQR-based outlier detection combined with a weighted mean — without any external data lookup, prediction, or professional assessment. Ideal for ML annotation pipelines, data quality audits, or labeling consistency reviews on small-to-medium batches (up to 200 rows) at minimal cost ($0.01 USDC for both reports).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T00:54:22.316Z","isFirstParty":false,"canonicalSlug":"label-review-analytics-iqr-outlier-flags-secondary-measure-weighted-123fdfb1"}