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{ "version": 1, "updatedAt": "2026-07-16T18:25:20.861Z", "boards": [], "cards": [], "assessments": [ { "id": "bb46e917-5403-47ef-966f-69f0e2845e25", "boardId": "6a510960bac709e025ae5c0f", "cardId": "6a5109eeff4650c50a156c10", "input": { "projectTypology": "ai_enabler", "lifecyclePhase": "data_preparation", "measurementMaturity": "defined", "approvalState": "draft", "metrics": { "modelPerformanceScore": 70, "dataReadinessScore": 55, "ethicalReviewCompleted": false, "legalReviewCompleted": false }, "risks": [ { "title": "Training data quality is insufficient", "dimension": "technical", "category": "technical", "lifecyclePhase": "data_preparation", "probability": 4, "impact": 5, "detectionDifficulty": 4, "mitigationCompleteness": 35, "mitigation": "Validate source data, define data quality thresholds, document missingness and bias checks, and attach evidence before model training continues.", "approvalState": "draft" } ] }, "score": { "projectTypology": "ai_enabler", "lifecyclePhase": "data_preparation", "measurementMaturity": "defined", "score": 29, "status": "medium", "averageMitigationCompleteness": 35, "dimensionTotals": { "organizational": 0, "technical": 52, "human": 0 }, "highestRisk": { "title": "Training data quality is insufficient", "category": "technical", "dimension": "technical", "lifecyclePhase": "data_preparation", "probability": 4, "impact": 5, "detectionDifficulty": 4, "mitigationCompleteness": 35, "owner": null, "dueDate": null, "mitigation": "Validate source data, define data quality thresholds, document missingness and bias checks, and attach evidence before model training continues.", "approvalState": "draft", "rawScore": 80, "residualScore": 52 }, "gate": { "deploymentReady": false, "blockingReasons": [ "Mitigation completeness is below 60%.", "Risk is not approved or accepted.", "Data readiness score is below 70%.", "Ethical review is not completed.", "Legal review is not completed." ] }, "risks": [ { "title": "Training data quality is insufficient", "category": "technical", "dimension": "technical", "lifecyclePhase": "data_preparation", "probability": 4, "impact": 5, "detectionDifficulty": 4, "mitigationCompleteness": 35, "owner": null, "dueDate": null, "mitigation": "Validate source data, define data quality thresholds, document missingness and bias checks, and attach evidence before model training continues.", "approvalState": "draft", "rawScore": 80, "residualScore": 52 } ], "interpretation": "Residual AI project risk is medium with a normalized score of 29/100. 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Deployment gate is blocked by 4 criterion or criteria." }, "createdAt": "2026-07-16T18:25:20.860Z", "updatedAt": "2026-07-16T18:25:20.860Z" } ] }
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