{"uid":"cap_bIy1CouvVQmxHbCqWQ6-b","slug":"review-aspect-prediction-error-records-04dbe3d5","name":"Review Aspect Prediction Error Records","description":"Review aspect - Prediction error records: Prediction error records 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 prediction error records deliverable.","url":"https://market.datapackvibe.com/x402/assistant-sector-ml-review-aspect-errors?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 supplied dataset.","actual":"performance","predicted":"performance","probabilities":[0.8,0.06666666666666667,0.06666666666666667,0.06666666666666667]},{"id":"example-0-1","text":"performance sample document number 1 for this supplied dataset.","actual":"performance","predicted":"performance","probabilities":[0.8,0.06666666666666667,0.06666666666666667,0.06666666666666667]},{"id":"example-0-2","text":"performance sample document number 2 for this supplied dataset.","actual":"performance","predicted":"performance","probabilities":[0.8,0.06666666666666667,0.06666666666666667,0.06666666666666667]},{"id":"example-1-0","text":"appearance sample document number 0 for this supplied dataset.","actual":"appearance","predicted":"appearance","probabilities":[0.06666666666666667,0.8,0.06666666666666667,0.06666666666666667]},{"id":"example-1-1","text":"appearance sample document number 1 for this supplied 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_t_lwhuYtRfA30FzTtgmFb","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":"Computes prediction error records for a review aspect classifier (performance/appearance/value/other) given up to 200 labelled text records with predicted probabilities.","exampleAgentPrompt":"I have a batch of 50 labelled product review texts where each record has the actual aspect (performance, appearance, value, or other), the predicted aspect, and the four class probabilities — can you run them through the review aspect prediction error records tool and show me which ones were misclassified?","exampleUseCases":[{"title":"Audit classifier mistakes on review dataset","prompt":"I've got 120 labelled review snippets for my aspect classifier — each one has the true label (performance, appearance, value, or other), the model's predicted label, and the four class probability scores. Can you compute the prediction error records so I can see exactly which records the model got wrong?"},{"title":"Compare model variants on shared test set","prompt":"I'm comparing two versions of my review aspect model and I want to see which records version B gets wrong. Here are 80 labelled records with their actual labels, predicted labels, and probability arrays — please run the prediction error records analysis and give me the full error breakdown."},{"title":"Debug low-confidence misclassifications","prompt":"My review aspect classifier seems to confuse 'value' and 'performance' reviews a lot. I have 200 labelled records with actual and predicted aspect labels and probability scores — can you compute the prediction error records so I can identify the systematic misclassification patterns?"}],"resultDescription":"A bounded deliverable containing prediction error records for up to 200 supplied labelled text instances, detailing which records were misclassified, the actual vs predicted aspect labels (performance/appearance/value/other), and associated probability scores to support local model evaluation and error analysis.","failureModes":["More than 200 records submitted — request rejected or truncated","Probabilities array does not contain exactly 4 values — validation error","Probabilities values outside [0,1] range — validation error","Missing required fields (id, text, actual, predicted, probabilities) — schema validation failure","Invalid enum value for actual or predicted (not one of performance/appearance/value/other) — error","Payment not processed — 402 response, no deliverable returned"],"whenToPreferThis":"Choose this endpoint when you need lightweight, local evaluation of a review aspect text classifier (covering performance, appearance, value, and other categories) without needing a hosted model or foundation-model fine-tuning. It is ideal for small-batch auditing (up to 200 records), debugging naive-Bayes or similar baselines, and producing bounded error records cheaply at $0.01 USDC per call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-12T00:40:48.868Z","isFirstParty":false,"canonicalSlug":"review-aspect-prediction-error-records-04dbe3d5"}