{"uid":"cap_FJ6lyxkyLSkV9JucxenJG","slug":"field-survey-coverage-string-normalisation-two-measure-correlation-fe58a0aa","name":"Field Survey Coverage — String Normalisation + Two-Measure Correlation","description":"Field survey coverage — String normalisation + Two-measure correlation: String normalisation + Two-measure correlation for supplied field survey coverage records (surveyed_m2, target_m2). 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-weather-22-033?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","station_group","date","surveyed_m2","target_m2"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"target_m2":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"surveyed_m2":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"station_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","target_m2":1,"surveyed_m2":10,"station_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","target_m2":2,"surveyed_m2":20,"station_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","target_m2":3,"surveyed_m2":15,"station_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","target_m2":4,"surveyed_m2":30,"station_group":"group-b"}],"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_ppEbolbrfHCob1xdnYJX8","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":"Normalises string fields and computes two-measure correlation across up to 200 field survey coverage records (surveyed_m2, target_m2), producing two independent analytical reports.","exampleAgentPrompt":"Can you normalise the station group strings and compute the correlation between surveyed_m2 and target_m2 for my field survey records? I have 4 rows: row-1 on 2026-10-01 for group-a with surveyed 10 m² and target 1 m², row-2 on 2026-10-02 for group-b with 20 m² surveyed and 2 m² target, row-3 on 2026-10-03 for group-a with 15 m² surveyed and 3 m² target, and row-4 on 2026-10-04 for group-b with 30 m² surveyed and 4 m² target.","exampleUseCases":[{"title":"Monitoring station coverage gap analysis","prompt":"I have survey records from 12 monitoring stations across two groups collected this month — can you normalise the station group names and tell me the correlation between how much area was actually surveyed versus the target coverage area? Here are the rows with row IDs, dates, station_group labels, surveyed_m2, and target_m2 values."},{"title":"Ecological survey completeness check","prompt":"We ran field surveys across 80 plots last quarter and I need to know how well our surveyed square metres tracked our target square metres — can you normalise the plot group strings and compute a two-measure correlation between surveyed_m2 and target_m2 for all 80 rows?"},{"title":"Infrastructure inspection coverage audit","prompt":"Can you clean up the zone group labels and calculate the correlation between the inspected area in m² and the planned target area in m² for these 150 inspection records from our last site survey?"}],"resultDescription":"Two independent reports: (1) a string normalisation report for the station_group and other string fields, and (2) a two-measure Pearson or equivalent correlation report between surveyed_m2 and target_m2 across all submitted rows. No external data is fetched; all analysis is performed locally on the supplied rows.","failureModes":["More than 200 rows submitted — request rejected or truncated","Missing required fields (row_id, date, surveyed_m2, target_m2) cause row-level validation errors","Date strings not matching YYYY-MM-DD pattern rejected","Null values in both numeric measures may produce undefined correlation","All rows in a single station_group may limit correlation meaningfulness"],"whenToPreferThis":"Choose this endpoint when you need both string field normalisation and a correlation analysis between two numeric coverage metrics (surveyed vs target area) on batch survey data up to 200 rows, without requiring any external lookups, predictions, or live data. It is particularly suited for field survey, environmental monitoring, or inspection datasets where station group label inconsistency and coverage-to-target tracking are simultaneous concerns.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T18:34:45.713Z","isFirstParty":false,"canonicalSlug":"field-survey-coverage-string-normalisation-two-measure-correlation-fe58a0aa"}