{"uid":"cap_poKD4R6TNRT2aNSV-xaHw","slug":"return-reason-low-confidence-review-queue-90110c29","name":"Return Reason Low-Confidence Review Queue","description":"Return reason - Low-confidence review queue: Low-confidence review queue for Return reason. Up to 200 supplied labelled text records. Local dataset tools, evaluation and small naive-Bayes baselines; no hosted model or foundation-model training. One of 25 profiles or calculations across 20 shared operations in this sector. 0.01 USDC includes one bounded low-confidence review queue deliverable.","url":"https://market.datapackvibe.com/x402/assistant-sector-ml-return-reason-review-queue?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"records":{"type":"array","items":{"type":"object","required":["id","text","actual","predicted","probabilities"],"properties":{"id":{"type":"string","default":"","maxLength":80,"minLength":1},"text":{"type":"string","default":"","maxLength":1000},"actual":{"enum":["damaged","wrong_item","unwanted","other"],"type":"string"},"predicted":{"enum":["damaged","wrong_item","unwanted","other"],"type":"string"},"probabilities":{"type":"array","items":{"type":"number","default":0,"maximum":1,"minimum":0},"default":[],"maxItems":4,"minItems":4}},"additionalProperties":false},"default":[{"id":"example-0-0","text":"damaged sample document number 0 for this supplied dataset.","actual":"damaged","predicted":"damaged","probabilities":[0.8,0.06666666666666667,0.06666666666666667,0.06666666666666667]},{"id":"example-0-1","text":"damaged sample document number 1 for this supplied dataset.","actual":"damaged","predicted":"damaged","probabilities":[0.8,0.06666666666666667,0.06666666666666667,0.06666666666666667]},{"id":"example-0-2","text":"damaged sample document number 2 for this supplied dataset.","actual":"damaged","predicted":"damaged","probabilities":[0.8,0.06666666666666667,0.06666666666666667,0.06666666666666667]},{"id":"example-1-0","text":"wrong_item sample document number 0 for this supplied dataset.","actual":"wrong_item","predicted":"wrong_item","probabilities":[0.06666666666666667,0.8,0.06666666666666667,0.06666666666666667]},{"id":"example-1-1","text":"wrong_item sample document number 1 for this supplied dataset.","actual":"wrong_item","predicted":"wrong_item","probabilities":[0.06666666666666667,0.8,0.06666666666666667,0.06666666666666667]},{"id":"example-1-2","text":"wrong_item sample document number 2 for this supplied dataset.","actual":"wrong_item","predicted":"wrong_item","probabilities":[0.06666666666666667,0.8,0.06666666666666667,0.06666666666666667]},{"id":"example-2-0","text":"unwanted sample document number 0 for this supplied dataset.","actual":"unwanted","predicted":"unwanted","probabilities":[0.06666666666666667,0.06666666666666667,0.8,0.06666666666666667]},{"id":"example-2-1","text":"unwanted sample document number 1 for this supplied dataset.","actual":"unwanted","predicted":"unwanted","probabilities":[0.06666666666666667,0.06666666666666667,0.8,0.06666666666666667]},{"id":"example-2-2","text":"unwanted sample document number 2 for this supplied dataset.","actual":"unwanted","predicted":"unwanted","probabilities":[0.06666666666666667,0.06666666666666667,0.8,0.06666666666666667]},{"id":"example-3-0","text":"other sample document number 0 for this supplied dataset.","actual":"other","predicted":"other","probabilities":[0.06666666666666667,0.06666666666666667,0.06666666666666667,0.8]},{"id":"example-3-1","text":"other sample document number 1 for this supplied dataset.","actual":"other","predicted":"other","probabilities":[0.06666666666666667,0.06666666666666667,0.06666666666666667,0.8]},{"id":"example-3-2","text":"other sample document number 2 for this supplied dataset.","actual":"other","predicted":"other","probabilities":[0.06666666666666667,0.06666666666666667,0.06666666666666667,0.8]}],"maxItems":200,"minItems":2},"minimum_confidence":{"type":"number","default":0.7,"maximum":1,"minimum":0}}},"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_LKcXhujIYDLO2i0OXJ6IJ","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":"Identifies low-confidence predictions in a return-reason classifier and returns a prioritized review queue from up to 200 labelled text records.","exampleAgentPrompt":"I ran my return-reason classifier on 150 customer return texts and I have the actual labels, predicted labels, and class probabilities for each one — can you send them through the low-confidence review queue to flag the uncertain predictions so I know which records to send to a human reviewer?","exampleUseCases":[{"title":"Flag uncertain return reason predictions for human review","prompt":"I have 120 labelled return records where my classifier predicted damaged, wrong_item, unwanted, or other, and I have the probabilities for each class. Can you run them through the low-confidence review queue so I get back only the ones the model was unsure about?"},{"title":"Audit classifier before deploying return automation","prompt":"Before I automate our returns routing, I want to check which predictions my return-reason model is least confident about. I have 200 records with actual labels, predicted labels, and four class probabilities each — can you generate a review queue of the low-confidence ones?"},{"title":"Prioritise QA effort on ambiguous return cases","prompt":"Our QA team only has time to manually review about 30 return reason cases this week. Can you take our 180 labelled records with predicted categories and probability scores and give us a review queue prioritising the most uncertain predictions?"}],"resultDescription":"A bounded review queue deliverable listing the submitted records that received low-confidence predictions, enabling targeted human review of ambiguous return reason classifications (damaged, wrong_item, unwanted, other). Includes up to 200 input records processed per call.","failureModes":["More than 200 records submitted — request rejected or truncated","Probability arrays not summing to 1 or not containing exactly 4 values — validation error","Invalid or missing enum values for actual/predicted fields — schema rejection","Empty records array — no review queue produced","Network or payment failure via x402 protocol — no response returned"],"whenToPreferThis":"Choose this endpoint when you have a trained return-reason text classifier outputting per-class probabilities and you need to surface low-confidence predictions for human review, quality assurance, or active learning — especially when working with small local datasets and naive-Bayes baselines rather than large hosted models. It is purpose-built for the damaged/wrong_item/unwanted/other taxonomy and provides a bounded, cost-effective single-call deliverable.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-12T00:54:37.307Z","isFirstParty":false,"canonicalSlug":"return-reason-low-confidence-review-queue-90110c29"}