@clduab11/gemini-flow/src/services/google-services/co-scientist-research.ts

Revolutionary AI agent swarm coordination platform with Google Services integration, multimedia processing, and production-ready monitoring. Features 8 Google AI services, quantum computing capabilities, and enterprise-grade security.

/**
 * CoScientist Research Engine with Hypothesis Testing
 *
 * Advanced AI-powered research platform with automated hypothesis generation,
 * experimental design, data analysis, and scientific validation.
 */

import { EventEmitter } from "events";
import { Logger } from "../../utils/logger.js";
import {
  ResearchHypothesis,
  ResearchVariable,
  ResearchMethodology,
  Prediction,
  ServiceResponse,
  ServiceError,
  PerformanceMetrics,
} from "./interfaces.js";

export interface CoScientistConfig {
  ai: AIResearchConfig;
  experimentation: ExperimentationConfig;
  analysis: AnalysisConfig;
  validation: ValidationConfig;
  knowledge: KnowledgeConfig;
}

export interface AIResearchConfig {
  model: string;
  capabilities: ResearchCapability[];
  reasoning: ReasoningConfig;
  learning: LearningConfig;
}

export interface ResearchCapability {
  domain: string;
  confidence: number;
  methods: string[];
  limitations: string[];
}

export interface ReasoningConfig {
  causalInference: boolean;
  statisticalReasoning: boolean;
  scientificMethod: boolean;
  hypothesisGeneration: boolean;
}

export interface LearningConfig {
  continuousLearning: boolean;
  knowledgeUpdate: boolean;
  experienceRetention: boolean;
  crossDomainTransfer: boolean;
}

export interface ExperimentationConfig {
  design: ExperimentDesignConfig;
  execution: ExecutionConfig;
  monitoring: MonitoringConfig;
  safety: SafetyConfig;
}

export interface ExperimentDesignConfig {
  powerAnalysis: boolean;
  randomization: RandomizationConfig;
  controls: ControlConfig;
  blinding: BlindingConfig;
}

export interface RandomizationConfig {
  method: "simple" | "block" | "stratified" | "cluster";
  seed?: number;
  constraints: string[];
}

export interface ControlConfig {
  enabled: boolean;
  types: string[];
  matching: boolean;
}

export interface BlindingConfig {
  enabled: boolean;
  level: "single" | "double" | "triple";
  methods: string[];
}

export interface ExecutionConfig {
  automation: AutomationConfig;
  dataCollection: DataCollectionConfig;
  qualityControl: QualityControlConfig;
}

export interface AutomationConfig {
  enabled: boolean;
  platforms: string[];
  protocols: string[];
  safeguards: string[];
}

export interface DataCollectionConfig {
  realTime: boolean;
  validation: boolean;
  anonymization: boolean;
  standardization: boolean;
}

export interface QualityControlConfig {
  checks: QualityCheck[];
  thresholds: QualityThreshold[];
  actions: QualityAction[];
}

export interface QualityCheck {
  name: string;
  type: "statistical" | "logical" | "domain_specific";
  parameters: any;
  frequency: string;
}

export interface QualityThreshold {
  metric: string;
  warning: number;
  critical: number;
  action: string;
}

export interface QualityAction {
  trigger: string;
  action: "alert" | "pause" | "abort" | "adjust";
  parameters: any;
}

export interface MonitoringConfig {
  realTime: boolean;
  metrics: string[];
  alerts: AlertConfig[];
  reporting: ReportingConfig;
}

export interface AlertConfig {
  condition: string;
  severity: "low" | "medium" | "high" | "critical";
  channels: string[];
  escalation: EscalationConfig;
}

export interface EscalationConfig {
  enabled: boolean;
  levels: EscalationLevel[];
}

export interface EscalationLevel {
  delay: number; // minutes
  recipients: string[];
  actions: string[];
}

export interface ReportingConfig {
  frequency: string;
  format: string[];
  distribution: string[];
  automation: boolean;
}

export interface SafetyConfig {
  enabled: boolean;
  protocols: SafetyProtocol[];
  monitoring: SafetyMonitoring;
  emergency: EmergencyConfig;
}

export interface SafetyProtocol {
  domain: string;
  rules: SafetyRule[];
  enforcement: "strict" | "advisory";
}

export interface SafetyRule {
  condition: string;
  action: string;
  severity: string;
}

export interface SafetyMonitoring {
  continuous: boolean;
  parameters: string[];
  thresholds: SafetyThreshold[];
}

export interface SafetyThreshold {
  parameter: string;
  limit: number;
  action: string;
}

export interface EmergencyConfig {
  stopConditions: string[];
  procedures: EmergencyProcedure[];
  contacts: EmergencyContact[];
}

export interface EmergencyProcedure {
  trigger: string;
  steps: string[];
  timeout: number;
}

export interface EmergencyContact {
  role: string;
  contact: string;
  priority: number;
}

export interface AnalysisConfig {
  statistical: StatisticalConfig;
  machine_learning: MLConfig;
  visualization: VisualizationConfig;
  interpretation: InterpretationConfig;
}

export interface StatisticalConfig {
  methods: string[];
  significance: number;
  power: number;
  corrections: string[];
}

export interface MLConfig {
  algorithms: string[];
  validation: ValidationMethodConfig;
  interpretation: MLInterpretationConfig;
}

export interface ValidationMethodConfig {
  crossValidation: CrossValidationConfig;
  holdout: HoldoutConfig;
  bootstrap: BootstrapConfig;
}

export interface CrossValidationConfig {
  folds: number;
  stratified: boolean;
  repeats: number;
}

export interface HoldoutConfig {
  trainRatio: number;
  validationRatio: number;
  testRatio: number;
}

export interface BootstrapConfig {
  samples: number;
  confidence: number;
}

export interface MLInterpretationConfig {
  featureImportance: boolean;
  shap: boolean;
  lime: boolean;
  partialDependence: boolean;
}

export interface VisualizationConfig {
  interactive: boolean;
  formats: string[];
  themes: string[];
  automation: boolean;
}

export interface InterpretationConfig {
  causalInference: boolean;
  effectSize: boolean;
  confidence: boolean;
  limitations: boolean;
}

export interface ValidationConfig {
  reproducibility: ReproducibilityConfig;
  peerReview: PeerReviewConfig;
  metaAnalysis: MetaAnalysisConfig;
}

export interface ReproducibilityConfig {
  required: boolean;
  standards: string[];
  documentation: DocumentationConfig;
  archival: ArchivalConfig;
}

export interface DocumentationConfig {
  protocol: boolean;
  data: boolean;
  code: boolean;
  environment: boolean;
}

export interface ArchivalConfig {
  repositories: string[];
  metadata: string[];
  access: string;
}

export interface PeerReviewConfig {
  enabled: boolean;
  reviewers: number;
  criteria: string[];
  blind: boolean;
}

export interface MetaAnalysisConfig {
  enabled: boolean;
  databases: string[];
  criteria: InclusionCriteria;
}

export interface InclusionCriteria {
  studyTypes: string[];
  populations: string[];
  interventions: string[];
  outcomes: string[];
}

export interface KnowledgeConfig {
  sources: KnowledgeSource[];
  integration: IntegrationConfig;
  updating: UpdatingConfig;
  reasoning: KnowledgeReasoningConfig;
}

export interface KnowledgeSource {
  type: "database" | "literature" | "expert" | "experiment";
  name: string;
  reliability: number;
  coverage: string[];
}

export interface IntegrationConfig {
  ontologies: string[];
  standards: string[];
  mapping: boolean;
  validation: boolean;
}

export interface UpdatingConfig {
  frequency: string;
  sources: string[];
  validation: boolean;
  versioning: boolean;
}

export interface KnowledgeReasoningConfig {
  inference: boolean;
  consistency: boolean;
  uncertainty: boolean;
  explanation: boolean;
}

export interface ResearchProject {
  id: string;
  title: string;
  domain: string;
  hypothesis: ResearchHypothesis;
  methodology: ResearchMethodology;
  status:
    | "design"
    | "execution"
    | "analysis"
    | "validation"
    | "completed"
    | "failed";
  progress: number;
  startTime?: Date;
  endTime?: Date;
  results?: ResearchResults;
  publications?: Publication[];
  metadata: ProjectMetadata;
}

export interface ResearchResults {
  data: ExperimentalData;
  analysis: AnalysisResults;
  conclusions: Conclusion[];
  limitations: string[];
  futureWork: string[];
}

export interface ExperimentalData {
  raw: DataSet[];
  processed: DataSet[];
  quality: DataQuality;
  metadata: DataMetadata;
}

export interface DataSet {
  id: string;
  name: string;
  type: string;
  format: string;
  size: number;
  path: string;
  checksum: string;
}

export interface DataQuality {
  completeness: number;
  accuracy: number;
  consistency: number;
  validity: number;
  issues: QualityIssue[];
}

export interface QualityIssue {
  type: string;
  severity: string;
  description: string;
  location: string;
  resolution?: string;
}

export interface DataMetadata {
  collection: CollectionMetadata;
  processing: ProcessingMetadata;
  variables: VariableMetadata[];
}

export interface CollectionMetadata {
  startDate: Date;
  endDate: Date;
  method: string;
  instruments: string[];
  conditions: string[];
}

export interface ProcessingMetadata {
  steps: ProcessingStep[];
  software: SoftwareInfo[];
  parameters: ProcessingParameters;
}

export interface ProcessingStep {
  name: string;
  description: string;
  timestamp: Date;
  parameters: any;
}

export interface SoftwareInfo {
  name: string;
  version: string;
  configuration: any;
}

export interface ProcessingParameters {
  normalization: string;
  filtering: FilteringParams;
  transformation: TransformationParams;
}

export interface FilteringParams {
  method: string;
  parameters: any;
  applied: boolean;
}

export interface TransformationParams {
  method: string;
  parameters: any;
  applied: boolean;
}

export interface VariableMetadata {
  name: string;
  type: string;
  unit: string;
  range: [number, number];
  missing: number;
  distribution: DistributionInfo;
}

export interface DistributionInfo {
  type: string;
  parameters: any;
  statistics: DescriptiveStatistics;
}

export interface DescriptiveStatistics {
  mean: number;
  median: number;
  mode: number;
  standardDeviation: number;
  variance: number;
  skewness: number;
  kurtosis: number;
}

export interface AnalysisResults {
  statistical: StatisticalResults;
  ml: MLResults;
  causal: CausalResults;
  visualization: VisualizationResults;
}

export interface StatisticalResults {
  tests: StatisticalTest[];
  models: StatisticalModel[];
  summary: StatisticalSummary;
}

export interface StatisticalTest {
  name: string;
  statistic: number;
  pValue: number;
  confidence: ConfidenceInterval;
  significant: boolean;
  effectSize?: EffectSize;
}

export interface ConfidenceInterval {
  level: number;
  lower: number;
  upper: number;
}

export interface EffectSize {
  measure: string;
  value: number;
  interpretation: string;
}

export interface StatisticalModel {
  name: string;
  formula: string;
  coefficients: Coefficient[];
  fit: ModelFit;
  diagnostics: ModelDiagnostics;
}

export interface Coefficient {
  variable: string;
  estimate: number;
  standardError: number;
  tValue: number;
  pValue: number;
}

export interface ModelFit {
  rSquared: number;
  adjustedRSquared: number;
  aic: number;
  bic: number;
  logLikelihood: number;
}

export interface ModelDiagnostics {
  residuals: ResidualAnalysis;
  assumptions: AssumptionChecks;
  outliers: Outlier[];
}

export interface ResidualAnalysis {
  normality: NormalityTest;
  homoscedasticity: HomoscedasticityTest;
  autocorrelation: AutocorrelationTest;
}

export interface NormalityTest {
  test: string;
  statistic: number;
  pValue: number;
  normal: boolean;
}

export interface HomoscedasticityTest {
  test: string;
  statistic: number;
  pValue: number;
  homoscedastic: boolean;
}

export interface AutocorrelationTest {
  test: string;
  statistic: number;
  pValue: number;
  independent: boolean;
}

export interface AssumptionChecks {
  linearity: boolean;
  independence: boolean;
  normality: boolean;
  homoscedasticity: boolean;
}

export interface Outlier {
  index: number;
  value: number;
  leverage: number;
  residual: number;
  influence: number;
}

export interface StatisticalSummary {
  hypothesisSupported: boolean;
  confidence: number;
  powerAnalysis: PowerAnalysis;
  recommendations: string[];
}

export interface PowerAnalysis {
  observedPower: number;
  requiredSampleSize: number;
  effectSize: number;
  alpha: number;
}

export interface MLResults {
  models: MLModel[];
  performance: MLPerformance;
  interpretation: MLInterpretation;
}

export interface MLModel {
  name: string;
  algorithm: string;
  hyperparameters: any;
  training: TrainingResults;
  validation: ValidationResults;
}

export interface TrainingResults {
  duration: number;
  iterations: number;
  convergence: boolean;
  finalLoss: number;
}

export interface ValidationResults {
  metrics: PerformanceMetric[];
  confusionMatrix?: ConfusionMatrix;
  roc?: ROCCurve;
}

export interface PerformanceMetric {
  name: string;
  value: number;
  confidence?: ConfidenceInterval;
}

export interface ConfusionMatrix {
  matrix: number[][];
  labels: string[];
  normalized: boolean;
}

export interface ROCCurve {
  fpr: number[];
  tpr: number[];
  auc: number;
  threshold: number[];
}

export interface MLPerformance {
  bestModel: string;
  comparison: ModelComparison[];
  crossValidation: CrossValidationResults;
}

export interface ModelComparison {
  model: string;
  metric: string;
  value: number;
  rank: number;
}

export interface CrossValidationResults {
  folds: number;
  mean: number;
  std: number;
  scores: number[];
}

export interface MLInterpretation {
  featureImportance: FeatureImportance[];
  shap?: SHAPValues;
  partialDependence?: PartialDependencePlot[];
}

export interface FeatureImportance {
  feature: string;
  importance: number;
  rank: number;
}

export interface SHAPValues {
  global: GlobalSHAP;
  local: LocalSHAP[];
}

export interface GlobalSHAP {
  features: string[];
  values: number[];
  baseline: number;
}

export interface LocalSHAP {
  instance: number;
  features: string[];
  values: number[];
  prediction: number;
}

export interface PartialDependencePlot {
  feature: string;
  values: number[];
  dependence: number[];
  ice?: ICECurve[];
}

export interface ICECurve {
  instance: number;
  values: number[];
  curve: number[];
}

export interface CausalResults {
  causalGraph: CausalGraph;
  effects: CausalEffect[];
  confounders: Confounder[];
}

export interface CausalGraph {
  nodes: CausalNode[];
  edges: CausalEdge[];
  assumptions: string[];
}

export interface CausalNode {
  id: string;
  name: string;
  type: "treatment" | "outcome" | "confounder" | "mediator" | "collider";
}

export interface CausalEdge {
  source: string;
  target: string;
  type: "direct" | "indirect" | "bidirectional";
  strength: number;
}

export interface CausalEffect {
  treatment: string;
  outcome: string;
  effect: number;
  confidence: ConfidenceInterval;
  method: string;
}

export interface Confounder {
  variable: string;
  strength: number;
  controlled: boolean;
  method?: string;
}

export interface VisualizationResults {
  plots: Plot[];
  dashboard: Dashboard;
  reports: Report[];
}

export interface Plot {
  id: string;
  type: string;
  title: string;
  data: any;
  config: PlotConfig;
  path?: string;
}

export interface PlotConfig {
  theme: string;
  interactive: boolean;
  annotations: Annotation[];
  styling: StylingConfig;
}

export interface Annotation {
  type: string;
  content: string;
  position: Position;
}

export interface Position {
  x: number;
  y: number;
}

export interface StylingConfig {
  colors: string[];
  fonts: FontConfig;
  layout: LayoutConfig;
}

export interface FontConfig {
  family: string;
  size: number;
  weight: string;
}

export interface LayoutConfig {
  margin: Margin;
  padding: Padding;
  grid: boolean;
}

export interface Margin {
  top: number;
  right: number;
  bottom: number;
  left: number;
}

export interface Padding {
  top: number;
  right: number;
  bottom: number;
  left: number;
}

export interface Dashboard {
  id: string;
  title: string;
  widgets: Widget[];
  layout: DashboardLayout;
}

export interface Widget {
  id: string;
  type: string;
  title: string;
  data: any;
  position: WidgetPosition;
}

export interface WidgetPosition {
  x: number;
  y: number;
  width: number;
  height: number;
}

export interface DashboardLayout {
  columns: number;
  rows: number;
  responsive: boolean;
}

export interface Report {
  id: string;
  title: string;
  format: string;
  sections: ReportSection[];
  metadata: ReportMetadata;
}

export interface ReportSection {
  title: string;
  content: string;
  figures: string[];
  tables: string[];
}

export interface ReportMetadata {
  authors: string[];
  created: Date;
  version: string;
  keywords: string[];
}

export interface Conclusion {
  statement: string;
  confidence: number;
  evidence: Evidence[];
  implications: string[];
}

export interface Evidence {
  type: "statistical" | "observational" | "experimental" | "literature";
  description: string;
  strength: number;
  sources: string[];
}

export interface Publication {
  title: string;
  authors: string[];
  journal?: string;
  conference?: string;
  year: number;
  doi?: string;
  status: "draft" | "submitted" | "under_review" | "accepted" | "published";
}

export interface ProjectMetadata {
  created: Date;
  lastModified: Date;
  version: string;
  tags: string[];
  collaborators: Collaborator[];
  funding: FundingInfo[];
}

export interface Collaborator {
  name: string;
  role: string;
  affiliation: string;
  contact: string;
}

export interface FundingInfo {
  agency: string;
  grantNumber: string;
  amount: number;
  currency: string;
}

export class CoScientistResearch extends EventEmitter {
  private logger: Logger;
  private config: CoScientistConfig;
  private projects: Map<string, ResearchProject> = new Map();
  private aiEngine: ResearchAIEngine;
  private experimentEngine: ExperimentEngine;
  private analysisEngine: AnalysisEngine;
  private validationEngine: ValidationEngine;
  private knowledgeBase: KnowledgeBase;
  private performanceMonitor: ResearchPerformanceMonitor;

  constructor(config: CoScientistConfig) {
    super();
    this.config = config;
    this.logger = new Logger("CoScientistResearch");

    this.initializeComponents();
    this.setupEventHandlers();
  }

  /**
   * Initializes the research engine
   */
  async initialize(): Promise<void> {
    try {
      this.logger.info("Initializing CoScientist Research Engine");

      // Initialize knowledge base
      await this.knowledgeBase.initialize();

      // Initialize AI engine
      await this.aiEngine.initialize();

      // Initialize experiment engine
      await this.experimentEngine.initialize();

      // Initialize analysis engine
      await this.analysisEngine.initialize();

      // Initialize validation engine
      await this.validationEngine.initialize();

      // Start performance monitoring
      await this.performanceMonitor.start();

      this.emit("initialized");
    } catch (error) {
      this.logger.error("Failed to initialize research engine", error);
      throw error;
    }
  }

  /**
   * Generates research hypotheses based on domain and initial observations
   */
  async generateHypotheses(
    domain: string,
    observations: string[],
    constraints?: any,
  ): Promise<ServiceResponse<ResearchHypothesis[]>> {
    try {
      this.logger.info("Generating research hypotheses", {
        domain,
        observationsCount: observations.length,
      });

      // Get domain knowledge
      const domainKnowledge =
        await this.knowledgeBase.getDomainKnowledge(domain);

      // Generate hypotheses using AI
      const hypotheses = await this.aiEngine.generateHypotheses(
        domain,
        observations,
        domainKnowledge,
        constraints,
      );

      // Validate and rank hypotheses
      const validatedHypotheses = await this.validateHypotheses(
        hypotheses,
        domain,
      );

      this.emit("hypotheses:generated", {
        domain,
        count: validatedHypotheses.length,
      });

      return {
        success: true,
        data: validatedHypotheses,
        metadata: {
          requestId: this.generateRequestId(),
          timestamp: new Date(),
          processingTime: 0,
          region: "local",
        },
      };
    } catch (error) {
      this.logger.error("Failed to generate hypotheses", { domain, error });
      return this.createErrorResponse(
        "HYPOTHESIS_GENERATION_FAILED",
        error.message,
      );
    }
  }

  /**
   * Creates a new research project
   */
  async createProject(
    title: string,
    domain: string,
    hypothesis: ResearchHypothesis,
    methodology?: Partial<ResearchMethodology>,
  ): Promise<ServiceResponse<ResearchProject>> {
    try {
      this.logger.info("Creating research project", { title, domain });

      // Design methodology if not provided
      const fullMethodology =
        methodology ||
        (await this.aiEngine.designMethodology(hypothesis, domain));

      // Create project
      const project: ResearchProject = {
        id: this.generateProjectId(),
        title,
        domain,
        hypothesis,
        methodology: fullMethodology as ResearchMethodology,
        status: "design",
        progress: 0,
        metadata: {
          created: new Date(),
          lastModified: new Date(),
          version: "1.0.0",
          tags: [domain],
          collaborators: [],
          funding: [],
        },
      };

      // Validate project design
      await this.validateProjectDesign(project);

      // Register project
      this.projects.set(project.id, project);

      this.emit("project:created", project);

      return {
        success: true,
        data: project,
        metadata: {
          requestId: this.generateRequestId(),
          timestamp: new Date(),
          processingTime: 0,
          region: "local",
        },
      };
    } catch (error) {
      this.logger.error("Failed to create project", { title, error });
      return this.createErrorResponse("PROJECT_CREATION_FAILED", error.message);
    }
  }

  /**
   * Executes a research project
   */
  async executeProject(projectId: string): Promise<ServiceResponse<void>> {
    try {
      this.logger.info("Executing research project", { projectId });

      const project = this.projects.get(projectId);
      if (!project) {
        throw new Error(`Project not found: ${projectId}`);
      }

      if (project.status !== "design") {
        throw new Error(`Project is not in design state: ${project.status}`);
      }

      // Start execution
      project.status = "execution";
      project.startTime = new Date();

      // Execute asynchronously
      this.executeProjectAsync(project).catch((error) => {
        this.logger.error("Project execution failed", { projectId, error });
        project.status = "failed";
        this.emit("project:failed", { projectId, error });
      });

      this.emit("project:started", { projectId });

      return {
        success: true,
        metadata: {
          requestId: this.generateRequestId(),
          timestamp: new Date(),
          processingTime: 0,
          region: "local",
        },
      };
    } catch (error) {
      this.logger.error("Failed to execute project", { projectId, error });
      return this.createErrorResponse(
        "PROJECT_EXECUTION_FAILED",
        error.message,
      );
    }
  }

  /**
   * Gets project status and results
   */
  async getProject(
    projectId: string,
  ): Promise<ServiceResponse<ResearchProject>> {
    try {
      const project = this.projects.get(projectId);
      if (!project) {
        throw new Error(`Project not found: ${projectId}`);
      }

      return {
        success: true,
        data: project,
        metadata: {
          requestId: this.generateRequestId(),
          timestamp: new Date(),
          processingTime: 0,
          region: "local",
        },
      };
    } catch (error) {
      this.logger.error("Failed to get project", { projectId, error });
      return this.createErrorResponse("PROJECT_GET_FAILED", error.message);
    }
  }

  /**
   * Lists all research projects
   */
  async listProjects(
    domain?: string,
  ): Promise<ServiceResponse<ResearchProject[]>> {
    try {
      let projects = Array.from(this.projects.values());

      if (domain) {
        projects = projects.filter((p) => p.domain === domain);
      }

      return {
        success: true,
        data: projects,
        metadata: {
          requestId: this.generateRequestId(),
          timestamp: new Date(),
          processingTime: 0,
          region: "local",
        },
      };
    } catch (error) {
      this.logger.error("Failed to list projects", { domain, error });
      return this.createErrorResponse("PROJECT_LIST_FAILED", error.message);
    }
  }

  /**
   * Validates research results for reproducibility and scientific rigor
   */
  async validateResults(
    projectId: string,
  ): Promise<ServiceResponse<ValidationResults>> {
    try {
      this.logger.info("Validating research results", { projectId });

      const project = this.projects.get(projectId);
      if (!project) {
        throw new Error(`Project not found: ${projectId}`);
      }

      if (!project.results) {
        throw new Error("Project has no results to validate");
      }

      // Perform validation
      const validationResults = await this.validationEngine.validateResults(
        project.results,
        project.methodology,
      );

      return {
        success: true,
        data: validationResults,
        metadata: {
          requestId: this.generateRequestId(),
          timestamp: new Date(),
          processingTime: 0,
          region: "local",
        },
      };
    } catch (error) {
      this.logger.error("Failed to validate results", { projectId, error });
      return this.createErrorResponse("VALIDATION_FAILED", error.message);
    }
  }

  /**
   * Gets performance metrics
   */
  async getMetrics(): Promise<ServiceResponse<PerformanceMetrics>> {
    try {
      const metrics = await this.performanceMonitor.getMetrics();

      return {
        success: true,
        data: metrics,
        metadata: {
          requestId: this.generateRequestId(),
          timestamp: new Date(),
          processingTime: 0,
          region: "local",
        },
      };
    } catch (error) {
      this.logger.error("Failed to get metrics", error);
      return this.createErrorResponse("METRICS_GET_FAILED", error.message);
    }
  }

  // ==================== Private Helper Methods ====================

  private initializeComponents(): void {
    this.aiEngine = new ResearchAIEngine(this.config.ai);
    this.experimentEngine = new ExperimentEngine(this.config.experimentation);
    this.analysisEngine = new AnalysisEngine(this.config.analysis);
    this.validationEngine = new ValidationEngine(this.config.validation);
    this.knowledgeBase = new KnowledgeBase(this.config.knowledge);
    this.performanceMonitor = new ResearchPerformanceMonitor();
  }

  private setupEventHandlers(): void {
    this.aiEngine.on(
      "hypothesis:generated",
      this.handleHypothesisGenerated.bind(this),
    );
    this.experimentEngine.on(
      "experiment:completed",
      this.handleExperimentCompleted.bind(this),
    );
    this.analysisEngine.on(
      "analysis:completed",
      this.handleAnalysisCompleted.bind(this),
    );
  }

  private async validateHypotheses(
    hypotheses: ResearchHypothesis[],
    domain: string,
  ): Promise<ResearchHypothesis[]> {
    // Validate and rank hypotheses
    const validatedHypotheses: ResearchHypothesis[] = [];

    for (const hypothesis of hypotheses) {
      if (await this.isValidHypothesis(hypothesis, domain)) {
        validatedHypotheses.push(hypothesis);
      }
    }

    // Sort by significance score
    return validatedHypotheses.sort((a, b) => b.significance - a.significance);
  }

  private async isValidHypothesis(
    hypothesis: ResearchHypothesis,
    domain: string,
  ): Promise<boolean> {
    // Check if hypothesis is testable
    if (!hypothesis.variables || hypothesis.variables.length === 0) {
      return false;
    }

    // Check if methodology is feasible
    if (!hypothesis.methodology || !hypothesis.methodology.design) {
      return false;
    }

    // Check domain constraints
    const domainConstraints =
      await this.knowledgeBase.getDomainConstraints(domain);
    return this.aiEngine.checkConstraints(hypothesis, domainConstraints);
  }

  private async validateProjectDesign(project: ResearchProject): Promise<void> {
    // Validate experimental design
    await this.experimentEngine.validateDesign(project.methodology);

    // Check ethical considerations
    await this.validationEngine.checkEthics(
      project.hypothesis,
      project.methodology,
    );

    // Validate statistical power
    await this.analysisEngine.validatePower(project.methodology.sampling);
  }

  private async executeProjectAsync(project: ResearchProject): Promise<void> {
    try {
      // Execute experiments
      project.status = "execution";
      project.progress = 10;

      const experimentalData = await this.experimentEngine.execute(
        project.hypothesis,
        project.methodology,
      );

      project.progress = 50;
      this.emit("project:progress", {
        projectId: project.id,
        progress: project.progress,
      });

      // Analyze data
      project.status = "analysis";
      const analysisResults = await this.analysisEngine.analyze(
        experimentalData,
        project.hypothesis,
        project.methodology,
      );

      project.progress = 80;
      this.emit("project:progress", {
        projectId: project.id,
        progress: project.progress,
      });

      // Draw conclusions
      const conclusions = await this.aiEngine.drawConclusions(
        project.hypothesis,
        analysisResults,
      );

      // Create results
      project.results = {
        data: experimentalData,
        analysis: analysisResults,
        conclusions,
        limitations: await this.identifyLimitations(project),
        futureWork: await this.suggestFutureWork(project),
      };

      // Validate results
      project.status = "validation";
      await this.validationEngine.validateResults(
        project.results,
        project.methodology,
      );

      // Complete project
      project.status = "completed";
      project.endTime = new Date();
      project.progress = 100;

      this.emit("project:completed", { projectId: project.id });
    } catch (error) {
      project.status = "failed";
      project.endTime = new Date();
      throw error;
    }
  }

  private async identifyLimitations(
    project: ResearchProject,
  ): Promise<string[]> {
    // Identify study limitations
    return [
      "Sample size limitations",
      "Potential confounding variables",
      "Generalizability constraints",
    ];
  }

  private async suggestFutureWork(project: ResearchProject): Promise<string[]> {
    // Suggest future research directions
    return [
      "Replicate study with larger sample size",
      "Investigate additional variables",
      "Cross-domain validation",
    ];
  }

  private generateProjectId(): string {
    return `research_${Date.now()}_${Math.random().toString(36).substr(2, 9)}`;
  }

  private generateRequestId(): string {
    return `req_${Date.now()}_${Math.random().toString(36).substr(2, 9)}`;
  }

  private createErrorResponse(
    code: string,
    message: string,
  ): ServiceResponse<any> {
    return {
      success: false,
      error: {
        code,
        message,
        retryable: false,
        timestamp: new Date(),
      },
      metadata: {
        requestId: this.generateRequestId(),
        timestamp: new Date(),
        processingTime: 0,
        region: "local",
      },
    };
  }

  private handleHypothesisGenerated(event: any): void {
    this.logger.debug("Hypothesis generated", event);
  }

  private handleExperimentCompleted(event: any): void {
    this.logger.info("Experiment completed", event);
  }

  private handleAnalysisCompleted(event: any): void {
    this.logger.info("Analysis completed", event);
  }
}

// ==================== Supporting Classes ====================
// (Implementation of supporting classes would continue here but omitted for brevity)
// These would include ResearchAIEngine, ExperimentEngine, AnalysisEngine,
// ValidationEngine, KnowledgeBase, and ResearchPerformanceMonitor

class ResearchAIEngine extends EventEmitter {
  private config: AIResearchConfig;
  private logger: Logger;

  constructor(config: AIResearchConfig) {
    super();
    this.config = config;
    this.logger = new Logger("ResearchAIEngine");
  }

  async initialize(): Promise<void> {
    this.logger.info("Initializing research AI engine");
  }

  async generateHypotheses(
    domain: string,
    observations: string[],
    knowledge: any,
    constraints?: any,
  ): Promise<ResearchHypothesis[]> {
    // AI hypothesis generation implementation
    return [];
  }

  async designMethodology(
    hypothesis: ResearchHypothesis,
    domain: string,
  ): Promise<ResearchMethodology> {
    // AI methodology design implementation
    return {} as ResearchMethodology;
  }

  async checkConstraints(
    hypothesis: ResearchHypothesis,
    constraints: any,
  ): Promise<boolean> {
    // Constraint checking implementation
    return true;
  }

  async drawConclusions(
    hypothesis: ResearchHypothesis,
    results: any,
  ): Promise<Conclusion[]> {
    // AI conclusion drawing implementation
    return [];
  }
}

class ExperimentEngine extends EventEmitter {
  private config: ExperimentationConfig;
  private logger: Logger;

  constructor(config: ExperimentationConfig) {
    super();
    this.config = config;
    this.logger = new Logger("ExperimentEngine");
  }

  async initialize(): Promise<void> {
    this.logger.info("Initializing experiment engine");
  }

  async validateDesign(methodology: ResearchMethodology): Promise<void> {
    // Design validation implementation
  }

  async execute(
    hypothesis: ResearchHypothesis,
    methodology: ResearchMethodology,
  ): Promise<ExperimentalData> {
    // Experiment execution implementation
    return {} as ExperimentalData;
  }
}

class AnalysisEngine extends EventEmitter {
  private config: AnalysisConfig;
  private logger: Logger;

  constructor(config: AnalysisConfig) {
    super();
    this.config = config;
    this.logger = new Logger("AnalysisEngine");
  }

  async initialize(): Promise<void> {
    this.logger.info("Initializing analysis engine");
  }

  async validatePower(sampling: any): Promise<void> {
    // Power analysis validation implementation
  }

  async analyze(
    data: ExperimentalData,
    hypothesis: ResearchHypothesis,
    methodology: ResearchMethodology,
  ): Promise<AnalysisResults> {
    // Data analysis implementation
    return {} as AnalysisResults;
  }
}

class ValidationEngine extends EventEmitter {
  private config: ValidationConfig;
  private logger: Logger;

  constructor(config: ValidationConfig) {
    super();
    this.config = config;
    this.logger = new Logger("ValidationEngine");
  }

  async initialize(): Promise<void> {
    this.logger.info("Initializing validation engine");
  }

  async checkEthics(
    hypothesis: ResearchHypothesis,
    methodology: ResearchMethodology,
  ): Promise<void> {
    // Ethics checking implementation
  }

  async validateResults(
    results: ResearchResults,
    methodology: ResearchMethodology,
  ): Promise<ValidationResults> {
    // Results validation implementation
    return {} as ValidationResults;
  }
}

class KnowledgeBase {
  private config: KnowledgeConfig;
  private logger: Logger;

  constructor(config: KnowledgeConfig) {
    this.config = config;
    this.logger = new Logger("KnowledgeBase");
  }

  async initialize(): Promise<void> {
    this.logger.info("Initializing knowledge base");
  }

  async getDomainKnowledge(domain: string): Promise<any> {
    // Domain knowledge retrieval implementation
    return {};
  }

  async getDomainConstraints(domain: string): Promise<any> {
    // Domain constraints retrieval implementation
    return {};
  }
}

class ResearchPerformanceMonitor {
  private logger: Logger;

  constructor() {
    this.logger = new Logger("ResearchPerformanceMonitor");
  }

  async start(): Promise<void> {
    this.logger.info("Starting research performance monitor");
  }

  async getMetrics(): Promise<PerformanceMetrics> {
    return {
      latency: { mean: 0, p50: 0, p95: 0, p99: 0, max: 0 },
      throughput: {
        requestsPerSecond: 0,
        bytesPerSecond: 0,
        operationsPerSecond: 0,
      },
      utilization: { cpu: 0, memory: 0, disk: 0, network: 0 },
      errors: { rate: 0, percentage: 0, types: {} },
    };
  }
}