{"uid":"cap_XJYtCVXJpaIYOhMwGqpsk","slug":"label-review-analytics-exact-row-deduplication-iqr-outlier-flags-8e7dced5","name":"Label Review Analytics: Exact Row Deduplication + IQR Outlier Flags","description":"Label review — Exact row deduplication + IQR outlier flags: Exact row deduplication + IQR outlier flags 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-12-049?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_EUmUOdVkLcxDlbdmx3yCO","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":"Deduplicates exact rows and flags IQR-based outliers in label review records containing reviewed_records and changed_labels fields, producing two independent analytical reports.","exampleAgentPrompt":"Can you run deduplication and IQR outlier detection on my label review records? Here are up to 200 rows with fields like row_id, dataset_group, date, reviewed_records, and changed_labels — I want both reports, and check outliers on the reviewed_records field.","exampleUseCases":[{"title":"Annotation pipeline data quality audit","prompt":"I have a batch of label review records from our annotation pipeline — each row has a row_id, dataset_group, date, reviewed_records, and changed_labels. Can you run exact row deduplication and flag any IQR outliers in the reviewed_records column so I can clean up the dataset before training?"},{"title":"Detecting anomalous label change spikes","prompt":"We track changed_labels daily across multiple dataset groups and I'm seeing some suspicious spikes. Can you take my label review rows and flag any IQR outliers in the changed_labels field, plus remove any exact duplicate rows that crept in?"},{"title":"Pre-release dataset consistency check","prompt":"Before we hand off this label review dataset to the model team, I need to confirm there are no exact duplicate rows and no statistical outliers in reviewed_records. Here are about 150 rows with row_id, date, dataset_group, reviewed_records, and changed_labels — please run both the dedup report and the IQR outlier analysis."}],"resultDescription":"Two independent analytical reports: (1) an exact row deduplication report identifying which rows are exact duplicates across all fields, and (2) an IQR outlier flags report identifying which rows have values in the selected field (reviewed_records or changed_labels) that fall outside the interquartile range bounds. Both reports are derived locally from the supplied data with no external lookups.","failureModes":["Input exceeds 200 rows — request will be rejected or truncated","Missing required fields (row_id, dataset_group, date, reviewed_records, or changed_labels) cause validation errors","Null numeric values in the target field may reduce outlier detection accuracy","Invalid date format (not YYYY-MM-DD) triggers schema validation failure","Insufficient data points for meaningful IQR calculation (very small row counts)"],"whenToPreferThis":"Choose this endpoint when you need fast, local, self-contained data quality checks on label review records specifically involving reviewed_records and changed_labels metrics. It is ideal for MLOps and annotation pipeline workflows where you want both deduplication and outlier detection in a single call without sending data to an external prediction or enrichment service. Prefer this over general-purpose analytics APIs when your dataset is under 200 rows and you need deterministic, reproducible results with no side effects.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:38:53.026Z","isFirstParty":false,"canonicalSlug":"label-review-analytics-exact-row-deduplication-iqr-outlier-flags-8e7dced5"}