{"uid":"cap_lVKIJ6ZxSJ_bxHHzQmLPy","slug":"support-intent-low-confidence-review-queue-f8746fd3","name":"Support Intent Low-Confidence Review Queue","description":"Support intent - Low-confidence review queue: Low-confidence review queue for Support intent. 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-support-intent-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":["billing","technical","account","other"],"type":"string"},"predicted":{"enum":["billing","technical","account","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":"billing sample document number 0 for this supplied dataset.","actual":"billing","predicted":"billing","probabilities":[0.8,0.06666666666666667,0.06666666666666667,0.06666666666666667]},{"id":"example-0-1","text":"billing sample document number 1 for this supplied dataset.","actual":"billing","predicted":"billing","probabilities":[0.8,0.06666666666666667,0.06666666666666667,0.06666666666666667]},{"id":"example-0-2","text":"billing sample document number 2 for this supplied dataset.","actual":"billing","predicted":"billing","probabilities":[0.8,0.06666666666666667,0.06666666666666667,0.06666666666666667]},{"id":"example-1-0","text":"technical sample document number 0 for this supplied dataset.","actual":"technical","predicted":"technical","probabilities":[0.06666666666666667,0.8,0.06666666666666667,0.06666666666666667]},{"id":"example-1-1","text":"technical sample document number 1 for this supplied dataset.","actual":"technical","predicted":"technical","probabilities":[0.06666666666666667,0.8,0.06666666666666667,0.06666666666666667]},{"id":"example-1-2","text":"technical sample document number 2 for this supplied dataset.","actual":"technical","predicted":"technical","probabilities":[0.06666666666666667,0.8,0.06666666666666667,0.06666666666666667]},{"id":"example-2-0","text":"account sample document number 0 for this supplied dataset.","actual":"account","predicted":"account","probabilities":[0.06666666666666667,0.06666666666666667,0.8,0.06666666666666667]},{"id":"example-2-1","text":"account sample document number 1 for this supplied dataset.","actual":"account","predicted":"account","probabilities":[0.06666666666666667,0.06666666666666667,0.8,0.06666666666666667]},{"id":"example-2-2","text":"account sample document number 2 for this supplied dataset.","actual":"account","predicted":"account","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_LSpBT8JWfG0BssMu1ZyHl","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 and surfaces low-confidence support ticket classifications (billing, technical, account, other) from a naive-Bayes model for human review.","exampleAgentPrompt":"I have up to 200 labeled support ticket records — each with an ID, the text, the actual intent label (billing, technical, account, or other), the predicted label, and four class probabilities — can you run them through the low-confidence review queue so I can see which ones the classifier was uncertain about and need human review?","exampleUseCases":[{"title":"Pre-retraining data audit","prompt":"Before I retrain my support intent classifier, I want to review the uncertain predictions — here are 150 labeled tickets with their actual intents, predicted intents, and probability scores across billing, technical, account, and other. Can you pull the low-confidence ones into a review queue so my team can relabel them?"},{"title":"Live classifier quality check","prompt":"My support bot's naive-Bayes model flagged some weird predictions this week. I have 80 records with IDs, text, actual labels, predicted labels, and probabilities — run them through the low-confidence review queue and tell me which cases are too uncertain to trust."},{"title":"Routing error triage","prompt":"I need to catch support tickets that got routed to the wrong category. I've got 120 records with actual vs predicted labels and class probabilities for billing, technical, account, and other — can you put the low-confidence or mismatched ones in a review queue so I know which to investigate?"}],"resultDescription":"A bounded deliverable (up to 200 records processed) identifying which submitted support text records fell below confidence thresholds in the naive-Bayes classifier, surfaced as a low-confidence review queue with flagged record IDs, their predicted and actual labels, and associated probability scores — ready for human review or relabeling.","failureModes":["More than 200 records submitted — endpoint enforces a hard cap","Probabilities array does not have exactly 4 elements per record — schema validation failure","Label values outside the allowed enum (billing, technical, account, other) cause rejection","Record ID missing or empty string triggers validation error","Text field exceeds 1000-character limit per record"],"whenToPreferThis":"Choose this endpoint when you have a labeled support-intent dataset (up to 200 records) and want to identify which naive-Bayes predictions are low-confidence for human review, without needing a hosted model or foundation-model training. Ideal for QA loops before classifier retraining or auditing routing accuracy on small local datasets.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-12T00:55:48.769Z","isFirstParty":false,"canonicalSlug":"support-intent-low-confidence-review-queue-f8746fd3"}