{"uid":"cap_8lGQhTzI676tU2Sg4oeYp","slug":"content-purpose-classifier-low-confidence-review-queue-5a9819fc","name":"Content Purpose Classifier – Low-Confidence Review Queue","description":"Content purpose - Low-confidence review queue: Low-confidence review queue for Content purpose. 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-content-purpose-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":["inform","explain","persuade","instruct"],"type":"string"},"predicted":{"enum":["inform","explain","persuade","instruct"],"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":"inform sample document number 0 for this supplied dataset.","actual":"inform","predicted":"inform","probabilities":[0.8,0.06666666666666667,0.06666666666666667,0.06666666666666667]},{"id":"example-0-1","text":"inform sample document number 1 for this supplied dataset.","actual":"inform","predicted":"inform","probabilities":[0.8,0.06666666666666667,0.06666666666666667,0.06666666666666667]},{"id":"example-0-2","text":"inform sample document number 2 for this supplied dataset.","actual":"inform","predicted":"inform","probabilities":[0.8,0.06666666666666667,0.06666666666666667,0.06666666666666667]},{"id":"example-1-0","text":"explain sample document number 0 for this supplied dataset.","actual":"explain","predicted":"explain","probabilities":[0.06666666666666667,0.8,0.06666666666666667,0.06666666666666667]},{"id":"example-1-1","text":"explain sample document number 1 for this supplied dataset.","actual":"explain","predicted":"explain","probabilities":[0.06666666666666667,0.8,0.06666666666666667,0.06666666666666667]},{"id":"example-1-2","text":"explain sample document number 2 for this supplied dataset.","actual":"explain","predicted":"explain","probabilities":[0.06666666666666667,0.8,0.06666666666666667,0.06666666666666667]},{"id":"example-2-0","text":"persuade sample document number 0 for this supplied dataset.","actual":"persuade","predicted":"persuade","probabilities":[0.06666666666666667,0.06666666666666667,0.8,0.06666666666666667]},{"id":"example-2-1","text":"persuade sample document number 1 for this supplied dataset.","actual":"persuade","predicted":"persuade","probabilities":[0.06666666666666667,0.06666666666666667,0.8,0.06666666666666667]},{"id":"example-2-2","text":"persuade sample document number 2 for this supplied dataset.","actual":"persuade","predicted":"persuade","probabilities":[0.06666666666666667,0.06666666666666667,0.8,0.06666666666666667]},{"id":"example-3-0","text":"instruct sample document number 0 for this supplied dataset.","actual":"instruct","predicted":"instruct","probabilities":[0.06666666666666667,0.06666666666666667,0.06666666666666667,0.8]},{"id":"example-3-1","text":"instruct sample document number 1 for this supplied dataset.","actual":"instruct","predicted":"instruct","probabilities":[0.06666666666666667,0.06666666666666667,0.06666666666666667,0.8]},{"id":"example-3-2","text":"instruct sample document number 2 for this supplied dataset.","actual":"instruct","predicted":"instruct","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_CtlKgb8bSW6CIEzd1W2eZ","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 content-purpose classifier and returns a structured review queue of up to 200 labelled text records for human inspection.","exampleAgentPrompt":"I have up to 200 labelled text records with actual and predicted content-purpose labels (inform, explain, persuade, instruct) and their class probabilities — can you run them through the low-confidence review queue to flag the ones the model was most uncertain about?","exampleUseCases":[{"title":"QA pipeline for content classifier","prompt":"We just ran our naive-Bayes content-purpose model over 150 articles and got back predicted labels and probabilities for each — can you push them all through the low-confidence review queue so I know which ones a human editor should double-check before we publish?"},{"title":"Auditing persuade vs instruct confusion","prompt":"My classifier keeps mixing up 'persuade' and 'instruct' labels on some documents. I have the record IDs, texts, actual labels, predicted labels, and probabilities for about 80 records — run them through the low-confidence review queue and tell me which ones scored below threshold."},{"title":"Pre-launch model validation","prompt":"Before we ship this content-purpose classifier, I want to surface any borderline cases. I'll give you the full set of 200 labelled examples with their probability outputs — queue up all the low-confidence ones so the team can review and relabel them if needed."}],"resultDescription":"A bounded deliverable listing the subset of submitted records where the classifier's predicted content-purpose label (inform, explain, persuade, instruct) fell below confidence thresholds, enabling targeted human review and relabelling. Includes flagged record IDs, texts, actual vs predicted labels, and associated probabilities.","failureModes":["More than 200 records submitted — input exceeds the maximum batch size","Probabilities array does not contain exactly 4 values per record — schema validation error","Probabilities values outside [0,1] range — rejected at input validation","Missing required fields (id, text, actual, predicted, probabilities) — schema validation failure","Label values outside allowed enum (inform, explain, persuade, instruct) — rejection","Empty records array — no output produced"],"whenToPreferThis":"Choose this endpoint when you have a local content-purpose text classification dataset with predicted labels and class probabilities and want to automatically surface the low-confidence cases for human review. It is ideal for human-in-the-loop QA workflows, pre-deployment audits, or iterative relabelling pipelines where you need a bounded, cost-effective review queue without hosting a model or calling a foundation model API.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-12T00:53:34.900Z","isFirstParty":false,"canonicalSlug":"content-purpose-classifier-low-confidence-review-queue-5a9819fc"}