102e05c8ba
Adds a full simulation harness (game-simulation package) with greedy/random strategies, 36-metric diagnostics, multi-run orchestration via child processes, and a statistical interpreter. Includes 2.3x engine performance optimizations (research bonus caching, per-DC dirty tracking, reduced allocations in tick pipeline, single-pass loops). Fixes a critical balance bug where training pipelines stalled on insufficient VRAM would permanently block training slots — the engine never re-checked stalled pipelines, and the greedy strategy didn't pre-check VRAM requirements. This caused 20-25% of seeds to get stuck in Scale-up era. All three fixes (engine un-stalling, strategy VRAM pre-check, stalled pipeline cancellation) bring pass rate from 75% to 100% across 20 random seeds. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
384 lines
15 KiB
TypeScript
384 lines
15 KiB
TypeScript
import { readFileSync } from 'node:fs';
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import { writeFileSync } from 'node:fs';
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const args = process.argv.slice(2);
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function getArg(name: string, defaultValue: string): string {
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const idx = args.indexOf(`--${name}`);
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return idx !== -1 && args[idx + 1] ? args[idx + 1] : defaultValue;
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}
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const summaryPath = getArg('summary', '');
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const outPath = getArg('out', '');
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if (!summaryPath) {
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console.error('Usage: interpret --summary <path-to-multirun-summary.csv> [--out <path>]');
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process.exit(1);
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}
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interface SummaryRow {
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runId: number;
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seed: number;
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passed: boolean;
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wallTimeMs: number;
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finalEra: string;
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finalMoney: number;
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finalRevenue: number;
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finalTotalRevenue: number;
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finalCapability: number;
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finalReputation: number;
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finalSubscribers: number;
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finalDevelopers: number;
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finalHeadcount: number;
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finalResearchCount: number;
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finalModelsDeployed: number;
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revenueStreamDiversity: number;
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featureUtilization: Record<string, number>;
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interconnectionOverall: number;
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interconnections: Record<string, number>;
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eraTransition_scaleup: number | null;
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eraTransition_bigtech: number | null;
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eraTransition_agi: number | null;
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bankruptcyRisks: number;
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sanityErrors: number;
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failureReasons: string;
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}
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function parseSummaryCsv(content: string): SummaryRow[] {
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const lines = content.trim().split('\n');
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if (lines.length < 2) return [];
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const headers = lines[0].split(',');
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const rows: SummaryRow[] = [];
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for (let i = 1; i < lines.length; i++) {
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const values = parseCSVLine(lines[i]);
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const get = (name: string): string => values[headers.indexOf(name)] ?? '';
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const num = (name: string): number => { const v = get(name); return v === '' ? 0 : Number(v); };
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const fuCategories: Record<string, number> = {};
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const icLinks: Record<string, number> = {};
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for (let h = 0; h < headers.length; h++) {
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if (headers[h].startsWith('featureUtilization_')) {
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fuCategories[headers[h].replace('featureUtilization_', '')] = Number(values[h]) || 0;
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}
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if (headers[h].startsWith('interconnection_') && headers[h] !== 'interconnection_overall') {
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icLinks[headers[h].replace('interconnection_', '')] = Number(values[h]) || 0;
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}
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}
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rows.push({
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runId: num('runId'),
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seed: num('seed'),
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passed: num('passed') === 1,
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wallTimeMs: num('wallTimeMs'),
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finalEra: get('finalEra'),
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finalMoney: num('finalMoney'),
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finalRevenue: num('finalRevenue'),
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finalTotalRevenue: num('finalTotalRevenue'),
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finalCapability: num('finalCapability'),
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finalReputation: num('finalReputation'),
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finalSubscribers: num('finalSubscribers'),
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finalDevelopers: num('finalDevelopers'),
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finalHeadcount: num('finalHeadcount'),
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finalResearchCount: num('finalResearchCount'),
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finalModelsDeployed: num('finalModelsDeployed'),
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revenueStreamDiversity: num('revenueStreamDiversity'),
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featureUtilization: fuCategories,
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interconnectionOverall: num('interconnection_overall'),
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interconnections: icLinks,
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eraTransition_scaleup: get('eraTransition_scaleup') ? num('eraTransition_scaleup') : null,
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eraTransition_bigtech: get('eraTransition_bigtech') ? num('eraTransition_bigtech') : null,
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eraTransition_agi: get('eraTransition_agi') ? num('eraTransition_agi') : null,
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bankruptcyRisks: num('bankruptcyRisks'),
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sanityErrors: num('sanityErrors'),
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failureReasons: get('failureReasons').replace(/^"|"$/g, ''),
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});
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}
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return rows;
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}
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function parseCSVLine(line: string): string[] {
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const values: string[] = [];
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let current = '';
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let inQuotes = false;
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for (let i = 0; i < line.length; i++) {
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const ch = line[i];
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if (inQuotes) {
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if (ch === '"' && line[i + 1] === '"') {
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current += '"';
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i++;
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} else if (ch === '"') {
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inQuotes = false;
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} else {
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current += ch;
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}
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} else {
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if (ch === '"') {
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inQuotes = true;
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} else if (ch === ',') {
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values.push(current);
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current = '';
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} else {
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current += ch;
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}
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}
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}
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values.push(current);
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return values;
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}
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interface Stats {
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mean: number;
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median: number;
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stddev: number;
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min: number;
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max: number;
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p5: number;
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p95: number;
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cv: number;
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}
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function computeStats(values: number[]): Stats {
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if (values.length === 0) return { mean: 0, median: 0, stddev: 0, min: 0, max: 0, p5: 0, p95: 0, cv: 0 };
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const sorted = [...values].sort((a, b) => a - b);
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const n = sorted.length;
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const mean = sorted.reduce((a, b) => a + b, 0) / n;
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const median = n % 2 === 0 ? (sorted[n / 2 - 1] + sorted[n / 2]) / 2 : sorted[Math.floor(n / 2)];
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const variance = sorted.reduce((sum, v) => sum + (v - mean) ** 2, 0) / n;
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const stddev = Math.sqrt(variance);
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const min = sorted[0];
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const max = sorted[n - 1];
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const p5 = sorted[Math.floor(n * 0.05)] ?? min;
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const p95 = sorted[Math.min(Math.floor(n * 0.95), n - 1)] ?? max;
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const cv = mean !== 0 ? stddev / Math.abs(mean) : 0;
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return { mean, median, stddev, min, max, p5, p95, cv };
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}
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function fmtNum(n: number, decimals = 1): string {
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if (Math.abs(n) >= 1e9) return `${(n / 1e9).toFixed(decimals)}B`;
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if (Math.abs(n) >= 1e6) return `${(n / 1e6).toFixed(decimals)}M`;
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if (Math.abs(n) >= 1e3) return `${(n / 1e3).toFixed(decimals)}K`;
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return n.toFixed(decimals);
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}
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function pad(s: string, w: number): string {
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return s.padEnd(w);
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}
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function formatDuration(ticks: number): string {
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const totalMinutes = Math.floor(ticks / 60);
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if (totalMinutes < 60) return `${totalMinutes}m`;
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const hours = Math.floor(totalMinutes / 60);
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const mins = totalMinutes % 60;
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return mins > 0 ? `${hours}h ${mins}m` : `${hours}h`;
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}
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function statsLine(label: string, s: Stats, formatter: (n: number) => string = n => fmtNum(n)): string {
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const cvFlag = s.cv > 0.3 ? ' [HIGH VARIANCE]' : '';
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return ` ${pad(label, 22)} mean=${pad(formatter(s.mean), 10)} median=${pad(formatter(s.median), 10)} stddev=${pad(formatter(s.stddev), 10)} range=[${formatter(s.min)}, ${formatter(s.max)}] p5=${formatter(s.p5)} p95=${formatter(s.p95)} CV=${s.cv.toFixed(2)}${cvFlag}`;
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}
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function generateReport(rows: SummaryRow[]): string {
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const lines: string[] = [];
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const n = rows.length;
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lines.push('=== Multi-Run Interpretation Report ===');
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lines.push('');
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// 1. Run Overview
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const passCount = rows.filter(r => r.passed).length;
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const totalWallTime = rows.reduce((s, r) => s + r.wallTimeMs, 0);
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lines.push('1. RUN OVERVIEW');
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lines.push(` Total runs: ${n}`);
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lines.push(` Pass rate: ${passCount}/${n} (${((passCount / n) * 100).toFixed(0)}%)`);
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lines.push(` Total wall time: ${(totalWallTime / 1000).toFixed(0)}s (avg ${(totalWallTime / n / 1000).toFixed(1)}s per run)`);
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const failedRuns = rows.filter(r => !r.passed);
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if (failedRuns.length > 0) {
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lines.push(` Failed seeds: ${failedRuns.map(r => r.seed).join(', ')}`);
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}
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lines.push('');
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// 2. Statistical Summaries
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lines.push('2. KEY METRICS');
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const metricDefs: Array<{ label: string; getter: (r: SummaryRow) => number; fmt?: (n: number) => string }> = [
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{ label: 'Final Money', getter: r => r.finalMoney, fmt: n => `$${fmtNum(n)}` },
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{ label: 'Final Revenue/tick', getter: r => r.finalRevenue, fmt: n => `$${fmtNum(n)}` },
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{ label: 'Total Revenue', getter: r => r.finalTotalRevenue, fmt: n => `$${fmtNum(n)}` },
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{ label: 'Capability', getter: r => r.finalCapability, fmt: n => n.toFixed(1) },
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{ label: 'Reputation', getter: r => r.finalReputation, fmt: n => n.toFixed(1) },
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{ label: 'Subscribers', getter: r => r.finalSubscribers, fmt: n => fmtNum(n, 0) },
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{ label: 'API Developers', getter: r => r.finalDevelopers, fmt: n => fmtNum(n, 0) },
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{ label: 'Headcount', getter: r => r.finalHeadcount, fmt: n => String(Math.round(n)) },
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{ label: 'Research Count', getter: r => r.finalResearchCount, fmt: n => String(Math.round(n)) },
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{ label: 'Models Deployed', getter: r => r.finalModelsDeployed, fmt: n => String(Math.round(n)) },
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{ label: 'Revenue Streams', getter: r => r.revenueStreamDiversity, fmt: n => String(Math.round(n)) },
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];
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const highVarianceMetrics: string[] = [];
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for (const def of metricDefs) {
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const values = rows.map(def.getter);
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const s = computeStats(values);
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lines.push(statsLine(def.label, s, def.fmt));
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if (s.cv > 0.3) highVarianceMetrics.push(def.label);
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}
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lines.push('');
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// 3. Era Transition Timing
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lines.push('3. ERA TRANSITION TIMING');
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const eraTransitions: Array<{ label: string; getter: (r: SummaryRow) => number | null }> = [
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{ label: 'Startup → Scale-up', getter: r => r.eraTransition_scaleup },
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{ label: 'Scale-up → Big Tech', getter: r => r.eraTransition_bigtech },
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{ label: 'Big Tech → AGI', getter: r => r.eraTransition_agi },
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];
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const inconsistentEras: string[] = [];
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for (const et of eraTransitions) {
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const values = rows.map(et.getter).filter((v): v is number => v !== null);
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const reached = values.length;
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if (reached === 0) {
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lines.push(` ${pad(et.label, 24)} never reached`);
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continue;
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}
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const s = computeStats(values);
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const cvFlag = s.cv > 0.25 ? ' [INCONSISTENT]' : '';
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if (s.cv > 0.25) inconsistentEras.push(et.label);
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lines.push(` ${pad(et.label, 24)} ${reached}/${n} reached | mean=${formatDuration(s.mean).padStart(6)} median=${formatDuration(s.median).padStart(6)} stddev=${Math.round(s.stddev).toString().padStart(5)}t range=[${formatDuration(s.min)}, ${formatDuration(s.max)}] CV=${s.cv.toFixed(2)}${cvFlag}`);
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}
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lines.push('');
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// 4. Feature Utilization Consistency
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lines.push('4. FEATURE UTILIZATION');
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const fuCategories = Object.keys(rows[0]?.featureUtilization ?? {});
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const consistentlyLow: string[] = [];
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for (const cat of fuCategories) {
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const values = rows.map(r => r.featureUtilization[cat] ?? 0);
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const s = computeStats(values);
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const bar = '#'.repeat(Math.round(s.mean / 5)) + '-'.repeat(20 - Math.round(s.mean / 5));
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const flag = s.mean < 50 ? ' [LOW]' : '';
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if (s.mean < 50) consistentlyLow.push(cat);
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lines.push(` ${pad(cat, 16)} [${bar}] mean=${s.mean.toFixed(0)}% stddev=${s.stddev.toFixed(1)}${flag}`);
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}
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lines.push('');
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// 5. System Interconnections
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lines.push('5. SYSTEM INTERCONNECTIONS');
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const icKeys = Object.keys(rows[0]?.interconnections ?? {});
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const weakLinks: string[] = [];
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const deadLinks: string[] = [];
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const inconsistentLinks: string[] = [];
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{
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const overallValues = rows.map(r => r.interconnectionOverall);
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const overallStats = computeStats(overallValues);
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lines.push(` Overall score: mean=${overallStats.mean.toFixed(1)} stddev=${overallStats.stddev.toFixed(1)} range=[${overallStats.min.toFixed(1)}, ${overallStats.max.toFixed(1)}]`);
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}
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for (const key of icKeys) {
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const values = rows.map(r => r.interconnections[key] ?? 0);
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const s = computeStats(values);
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const label = key.replace(/_/g, ' → ').replace(/([a-z])([A-Z])/g, '$1 $2');
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const bar = '#'.repeat(Math.round(s.mean)) + '-'.repeat(10 - Math.round(s.mean));
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let flag = '';
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if (s.mean === 0) { flag = ' [DEAD]'; deadLinks.push(label); }
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else if (s.mean < 3) { flag = ' [WEAK]'; weakLinks.push(label); }
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if (s.stddev > 3) { flag += ' [INCONSISTENT]'; inconsistentLinks.push(label); }
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lines.push(` ${pad(label, 30)} [${bar}] mean=${s.mean.toFixed(1)} stddev=${s.stddev.toFixed(1)} min=${s.min}${flag}`);
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}
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lines.push('');
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// 6. Failure Analysis
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lines.push('6. FAILURE ANALYSIS');
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const failureFreq: Record<string, number> = {};
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for (const r of rows) {
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if (!r.failureReasons) continue;
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const seen = new Set<string>();
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for (const reason of r.failureReasons.split('; ').filter(Boolean)) {
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const normalized = reason.replace(/tick \d+/g, 'tick N').replace(/\d+ ticks/g, 'N ticks');
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seen.add(normalized);
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}
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for (const normalized of seen) {
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failureFreq[normalized] = (failureFreq[normalized] ?? 0) + 1;
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}
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}
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const sortedFailures = Object.entries(failureFreq).sort((a, b) => b[1] - a[1]);
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if (sortedFailures.length === 0) {
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lines.push(' No failures detected across all runs.');
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} else {
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for (const [reason, count] of sortedFailures.slice(0, 10)) {
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lines.push(` ${((count / n) * 100).toFixed(0).padStart(3)}% (${count}/${n}) ${reason}`);
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}
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}
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const bankruptcyRuns = rows.filter(r => r.bankruptcyRisks > 0).length;
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if (bankruptcyRuns > 0) {
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lines.push(` Bankruptcy risk: ${bankruptcyRuns}/${n} runs (${((bankruptcyRuns / n) * 100).toFixed(0)}%)`);
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}
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const sanityFailRuns = rows.filter(r => r.sanityErrors > 0).length;
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if (sanityFailRuns > 0) {
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lines.push(` Sanity errors: ${sanityFailRuns}/${n} runs (${((sanityFailRuns / n) * 100).toFixed(0)}%)`);
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}
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lines.push('');
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// 7. Actionable Recommendations
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lines.push('7. RECOMMENDATIONS');
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const recs: string[] = [];
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if (passCount / n < 0.8) {
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const topFailure = sortedFailures[0];
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if (topFailure) {
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recs.push(`Balance is unstable — "${topFailure[0]}" occurs in ${((topFailure[1] / n) * 100).toFixed(0)}% of runs. This is the top priority fix.`);
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}
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}
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for (const cat of consistentlyLow) {
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recs.push(`Feature category "${cat}" has <50% utilization on average — review whether ${cat} features are reachable and worthwhile for the strategy.`);
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}
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for (const link of deadLinks) {
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recs.push(`"${link}" has no measurable effect in any run — investment in the source doesn't translate to improvement in the target.`);
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}
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for (const link of weakLinks) {
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recs.push(`"${link}" is consistently weak (mean <3/10) — the connection exists but is too faint to drive strategy.`);
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}
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for (const metric of highVarianceMetrics) {
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const values = rows.map(metricDefs.find(d => d.label === metric)!.getter);
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const s = computeStats(values);
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recs.push(`"${metric}" is highly seed-dependent (CV=${s.cv.toFixed(2)}) — outcome is more luck than strategy. Consider tighter guardrails.`);
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}
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for (const era of inconsistentEras) {
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recs.push(`"${era}" transition timing is inconsistent (CV>0.25) — suggests a fragile threshold crossing that depends on RNG luck.`);
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}
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if (passCount === n && recs.length === 0) {
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recs.push('All runs passed with consistent results. Balance looks stable across seeds.');
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}
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for (let i = 0; i < recs.length; i++) {
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lines.push(` ${i + 1}. ${recs[i]}`);
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}
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lines.push('');
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return lines.join('\n');
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}
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const csvContent = readFileSync(summaryPath, 'utf-8');
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const rows = parseSummaryCsv(csvContent);
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if (rows.length === 0) {
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console.error('No data found in summary CSV.');
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process.exit(1);
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}
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const report = generateReport(rows);
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if (outPath) {
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writeFileSync(outPath, report);
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console.log(`Report written to ${outPath}`);
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} else {
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console.log(report);
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}
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