{"uid":"cap_3sUQgvshaLzoZOZ4EF2LB","slug":"review-aspect-label-and-prediction-audit-65799cda","name":"Review Aspect Label and Prediction Audit","description":"Review aspect - Label and prediction audit: Label and prediction audit for Review aspect. 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 label and prediction audit deliverable.","url":"https://market.datapackvibe.com/x402/assistant-sector-ml-review-aspect-label-audit?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":["performance","appearance","value","other"],"type":"string"},"predicted":{"enum":["performance","appearance","value","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":"performance sample document number 0 for this 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dataset.","actual":"appearance","predicted":"appearance","probabilities":[0.06666666666666667,0.8,0.06666666666666667,0.06666666666666667]},{"id":"example-1-2","text":"appearance sample document number 2 for this supplied dataset.","actual":"appearance","predicted":"appearance","probabilities":[0.06666666666666667,0.8,0.06666666666666667,0.06666666666666667]},{"id":"example-2-0","text":"value sample document number 0 for this supplied dataset.","actual":"value","predicted":"value","probabilities":[0.06666666666666667,0.06666666666666667,0.8,0.06666666666666667]},{"id":"example-2-1","text":"value sample document number 1 for this supplied dataset.","actual":"value","predicted":"value","probabilities":[0.06666666666666667,0.06666666666666667,0.8,0.06666666666666667]},{"id":"example-2-2","text":"value sample document number 2 for this supplied dataset.","actual":"value","predicted":"value","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}}},"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_cTT5Dh-fbKlMrf4U-6PBJ","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":"Audits classifier labels and predictions for review aspect classification (performance, appearance, value, other) across up to 200 labelled text records, computing evaluation metrics using naive-Bayes baselines.","exampleAgentPrompt":"I have 50 labelled product review sentences where each has an actual aspect label (performance, appearance, value, or other), a predicted label from my classifier, and four class probabilities — can you run a label and prediction audit on them to see where my model is going wrong?","exampleUseCases":[{"title":"E-commerce classifier quality check","prompt":"I've got 120 product reviews tagged with actual aspect categories — performance, appearance, value, or other — and my model's predicted labels and probabilities for each. Can you audit the predictions and tell me which aspect categories the model struggles with most?"},{"title":"Model regression testing after retraining","prompt":"We just retrained our review aspect classifier and I want to audit 180 labelled test records — each has the actual aspect, the new model's predicted aspect, and all four class probabilities. Run a prediction audit so I can compare the new model's error profile to baseline."},{"title":"Data quality review before model training","prompt":"Before we finalize our training dataset, can you audit these 75 labelled review records for aspect classification? I have actual labels, predicted labels from a quick model, and class probability vectors for each record — I want to catch any labelling inconsistencies or systematic errors."}],"resultDescription":"A bounded audit deliverable covering classification accuracy and error analysis for up to 200 review records labelled across four aspect categories (performance, appearance, value, other). Includes evaluation metrics comparing predicted vs actual labels, probability-based diagnostics, and naive-Bayes baseline comparisons computed locally without hosted model inference.","failureModes":["Exceeding 200 records per call returns an error or truncated results","Malformed probability arrays (not exactly 4 values summing near 1.0) may cause computation errors","Invalid or out-of-enum actual/predicted labels will fail schema validation","Empty records array produces no meaningful audit output","Missing required fields (id, text, actual, predicted, probabilities) per record causes rejection"],"whenToPreferThis":"Choose this endpoint when you need a fast, low-cost ($0.01) audit of a review aspect classifier's label quality and prediction accuracy on a small labelled dataset (up to 200 records) with four fixed categories (performance, appearance, value, other). Ideal for validating classifier outputs, catching labelling errors, or benchmarking against a naive-Bayes baseline without needing hosted model infrastructure or foundation model access.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T18:48:00.761Z","isFirstParty":false,"canonicalSlug":"review-aspect-label-and-prediction-audit-65799cda"}