{"uid":"cap_gCA9oVv6CeKFS_YG7z4_X","slug":"label-review-numeric-row-ordering-trailing-mean-series-721ccb5f","name":"Label Review — Numeric Row Ordering + Trailing Mean Series","description":"Label review — Numeric row ordering + Trailing mean series: Numeric row ordering + Trailing mean series 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-12-115?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"},"window":{"type":"integer","default":2,"maximum":200,"minimum":2}}},"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_b8qt8O6JEhZ5edX4kJ4D2","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":"Computes numeric row ordering and trailing mean series for label review records (reviewed_records and changed_labels) across up to 200 rows.","exampleAgentPrompt":"I have 4 label review records from October 2026 — can you run numeric row ordering and a trailing mean (window size 2) on the reviewed_records field? The rows are: row-1 group-a 2026-10-01 reviewed=10 changed=1, row-2 group-b 2026-10-02 reviewed=20 changed=2, row-3 group-a 2026-10-03 reviewed=15 changed=3, row-4 group-b 2026-10-04 reviewed=30 changed=4.","exampleUseCases":[{"title":"Trending annotation review volume","prompt":"I have daily label review records for two dataset groups over the past week — can you compute a trailing mean with a window of 3 on the reviewed_records field and also give me numeric row ordering so I can see which days had the most review activity?"},{"title":"Detecting label churn over time","prompt":"Run numeric row ordering and a trailing mean (window size 5) on my changed_labels data for these 20 label review rows — I want to smooth out noise and rank the rows to spot when label churn was highest."},{"title":"Comparing dataset groups in review pipeline","prompt":"I've got 50 label review records split across two dataset groups with dates from last month — can you rank them numerically and compute a trailing mean on reviewed_records with window 2 so I can compare trends between the groups?"}],"resultDescription":"Two analytical reports for the supplied label review rows: (1) a numeric row ordering that ranks each row by the selected metric, and (2) a trailing mean series that smooths the chosen field (reviewed_records or changed_labels) over the specified window size. Results are computed locally with no external lookups.","failureModes":["Fewer than 1 or more than 200 rows submitted — schema validation error","Invalid date format (not YYYY-MM-DD) — pattern validation failure","Window size less than 2 or greater than 200 — schema rejection","Field value not one of 'reviewed_records' or 'changed_labels' — enum validation error","Null numeric values in required fields may affect mean computation","Payment not completed — x402 payment required before response"],"whenToPreferThis":"Choose this endpoint when you need both numeric row ordering and a trailing mean series computed together on label review data (reviewed_records and changed_labels) in a single low-cost call. It is ideal for ML ops pipelines tracking annotation throughput and label change rates over time, especially when you want smoothed trend analysis without any external data enrichment or prediction.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T00:54:21.677Z","isFirstParty":false,"canonicalSlug":"label-review-numeric-row-ordering-trailing-mean-series-721ccb5f"}