{"uid":"cap_9Rb3WFu7XYAaOf2YGsBy-","slug":"task-type-low-confidence-review-queue-0118a664","name":"Task Type Low-Confidence Review Queue","description":"Task type - Low-confidence review queue: Low-confidence review queue for Task type. 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-task-type-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":["research","writing","analysis","implementation"],"type":"string"},"predicted":{"enum":["research","writing","analysis","implementation"],"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":"research sample document number 0 for this supplied dataset.","actual":"research","predicted":"research","probabilities":[0.8,0.06666666666666667,0.06666666666666667,0.06666666666666667]},{"id":"example-0-1","text":"research sample document number 1 for this supplied dataset.","actual":"research","predicted":"research","probabilities":[0.8,0.06666666666666667,0.06666666666666667,0.06666666666666667]},{"id":"example-0-2","text":"research sample document number 2 for this supplied dataset.","actual":"research","predicted":"research","probabilities":[0.8,0.06666666666666667,0.06666666666666667,0.06666666666666667]},{"id":"example-1-0","text":"writing sample document number 0 for this supplied dataset.","actual":"writing","predicted":"writing","probabilities":[0.06666666666666667,0.8,0.06666666666666667,0.06666666666666667]},{"id":"example-1-1","text":"writing sample document number 1 for this supplied dataset.","actual":"writing","predicted":"writing","probabilities":[0.06666666666666667,0.8,0.06666666666666667,0.06666666666666667]},{"id":"example-1-2","text":"writing sample document number 2 for this supplied dataset.","actual":"writing","predicted":"writing","probabilities":[0.06666666666666667,0.8,0.06666666666666667,0.06666666666666667]},{"id":"example-2-0","text":"analysis sample document number 0 for this supplied dataset.","actual":"analysis","predicted":"analysis","probabilities":[0.06666666666666667,0.06666666666666667,0.8,0.06666666666666667]},{"id":"example-2-1","text":"analysis sample document number 1 for this supplied dataset.","actual":"analysis","predicted":"analysis","probabilities":[0.06666666666666667,0.06666666666666667,0.8,0.06666666666666667]},{"id":"example-2-2","text":"analysis sample document number 2 for this supplied dataset.","actual":"analysis","predicted":"analysis","probabilities":[0.06666666666666667,0.06666666666666667,0.8,0.06666666666666667]},{"id":"example-3-0","text":"implementation sample document number 0 for this supplied dataset.","actual":"implementation","predicted":"implementation","probabilities":[0.06666666666666667,0.06666666666666667,0.06666666666666667,0.8]},{"id":"example-3-1","text":"implementation sample document number 1 for this supplied dataset.","actual":"implementation","predicted":"implementation","probabilities":[0.06666666666666667,0.06666666666666667,0.06666666666666667,0.8]},{"id":"example-3-2","text":"implementation sample document number 2 for this supplied dataset.","actual":"implementation","predicted":"implementation","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_C4uwb6jjJKdeMTTku0KCU","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 predictions from a naive-Bayes task-type classifier for human review, given up to 200 labelled text records with actual/predicted labels and class probabilities.","exampleAgentPrompt":"I have 200 labelled text records — each with an ID, the text, the actual task type (research, writing, analysis, or implementation), the predicted task type, and the four class probabilities — can you run them through the low-confidence review queue to surface which ones I should manually check?","exampleUseCases":[{"title":"QA audit of task classifier output","prompt":"Here are 150 records from our task-type classifier — each has the text, the actual label (research, writing, analysis, or implementation), the predicted label, and the four class probabilities. Can you generate a low-confidence review queue so our QA team knows which predictions to manually inspect?"},{"title":"Detecting borderline research vs analysis labels","prompt":"Our naive-Bayes model keeps confusing 'research' and 'analysis' tasks. I have 80 labelled records with actual labels, predicted labels, and probability scores — can you pull a low-confidence review queue so I can see which ones are most ambiguous?"},{"title":"Pre-training data cleaning for task classifier","prompt":"Before we retrain our task-type model, I want to weed out the uncertain samples from our 200-record training set. Each record has the text, actual and predicted labels, and four class probabilities — can you run the low-confidence review queue to flag the ones we should relabel first?"}],"resultDescription":"A bounded review queue deliverable listing up to 200 records identified as low-confidence by the naive-Bayes classifier, with associated metadata (IDs, text, actual vs predicted labels, probabilities) to guide human review and relabelling.","failureModes":["Fewer than 1 or more than 200 records supplied — request rejected","Records missing required fields (id, text, actual, predicted, probabilities) — validation error","Probabilities array does not contain exactly 4 values summing approximately to 1 — schema rejection","Invalid enum values for actual or predicted fields — rejected","Empty records array returns no meaningful review queue"],"whenToPreferThis":"Choose this endpoint when you have a local text dataset labelled with task types (research, writing, analysis, implementation) and need to identify which predictions from a naive-Bayes model are uncertain enough to warrant human review. It is ideal for data quality audits, pre-retraining cleaning, and lightweight evaluation workflows where no hosted model or foundation-model training is needed.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-12T00:43:19.212Z","isFirstParty":false,"canonicalSlug":"task-type-low-confidence-review-queue-0118a664"}