{"uid":"cap_DRLUy6zRJS7W1aTBCjTp1","slug":"research-sample-recovery-string-normalisation-561adc17","name":"Research Sample Recovery – String Normalisation","description":"Research sample recovery - String normalisation: String normalisation for Research sample recovery. Up to 200 supplied typed records. Local descriptive analytics; no enrichment or forecast. One of 25 new profiles across 20 shared operations in this industry. 0.01 USDC includes one bounded string normalisation report.","url":"https://market.datapackvibe.com/x402/assistant-ar-analytics-sample-recovery-normalise?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","specimen","date","input_mass_g","recovered_mass_g"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"specimen":{"type":"string","default":"","maxLength":80},"input_mass_g":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"recovered_mass_g":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","specimen":"group-a","input_mass_g":10,"recovered_mass_g":1},{"date":"2026-10-02","row_id":"row-2","specimen":"group-b","input_mass_g":20,"recovered_mass_g":2},{"date":"2026-10-03","row_id":"row-3","specimen":"group-a","input_mass_g":15,"recovered_mass_g":3},{"date":"2026-10-04","row_id":"row-4","specimen":"group-b","input_mass_g":30,"recovered_mass_g":4}],"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_nc6lEOZmwR7y0jaPk16Fj","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 (specimen names, identifiers, dates) across up to 200 research sample recovery records and returns a local descriptive analytics report.","exampleAgentPrompt":"Can you normalise the specimen name strings and clean up the date fields in my sample recovery records? I have about 50 rows, each with a row ID, specimen group label, date, input mass, and recovered mass — here's the batch.","exampleUseCases":[{"title":"Standardising specimen labels across lab batches","prompt":"I've got 120 sample recovery rows from our lab where specimen names are inconsistently typed — things like 'Group A', 'group-a', 'GROUP_A'. Can you normalise all those string fields and give me a descriptive analytics report?"},{"title":"Pre-analysis data cleaning for recovery rate study","prompt":"Before I run my recovery rate analysis, I need to clean up the specimen and date strings in these 80 records. Each row has a row ID, specimen name, date in YYYY-MM-DD format, input mass in grams, and recovered mass. Can you run string normalisation on the whole batch?"},{"title":"Auditing messy identifiers in a research dataset","prompt":"We collected 200 sample recovery entries over the past month but the row IDs and specimen labels are all over the place. Can you normalise the strings and return a summary report so I can see what got standardised?"}],"resultDescription":"A bounded string normalisation report covering up to 200 supplied records, with normalised string fields (specimen names, row IDs, dates) and local descriptive analytics summarising the dataset — no external enrichment or forecasting is included.","failureModes":["Fewer than 1 row supplied — request rejected","More than 200 rows supplied — exceeds maxItems limit","Date field does not match YYYY-MM-DD pattern — validation error","row_id missing or empty — required field error","mass values outside ±1 trillion range — schema validation failure","Payment of 0.01 USDC not completed — 402 Payment Required response"],"whenToPreferThis":"Choose this endpoint when you have a batch of up to 200 research sample recovery records with inconsistent or dirty string fields (specimen names, identifiers, dates) and need a lightweight, local normalisation plus descriptive summary — without requiring external data enrichment or predictive forecasting. Ideal for pre-processing lab data before downstream analysis.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-13T00:42:20.899Z","isFirstParty":false,"canonicalSlug":"research-sample-recovery-string-normalisation-561adc17"}