# The Chaos Signal Aggregator
def calculate_market_chaos_score():
    signals = {
        'fed_chair_footwear_formality': get_fed_footwear_index(),
        'tiktok_dance_complexity': analyze_trending_dances(),
        'celebrity_drama_intensity': scrape_tabloid_headlines(),
        'millennial_food_photography': count_instagram_food_posts(),
        'linkedin_motivation_posts': measure_professional_cringe()
    }
    
    chaos_score = sum(signals.values()) / len(signals)
    market_prediction = "buy puts" if chaos_score > 0.7 else "YOLO calls"
    
    return {
        'chaos_level': chaos_score,
        'trading_strategy': market_prediction,
        'confidence': '420.69%'  # Always this confident
    }

# The Academic Chart Generator
def generate_impressive_chart(your_theory, data_points):
    chart_config = {
        'title': f"Empirical Analysis of {your_theory} (N={len(data_points)})",
        'x_axis': "Time (Arbitrary Units)",
        'y_axis_primary': "Traditional Economic Indicator",
        'y_axis_secondary': "Your Conspiracy Metric",
        'correlation_coefficient': random.uniform(0.85, 0.97),
        'p_value': "< 0.001",  # Always highly significant
        'color_scheme': 'academic_intimidation',
        'font': 'Times New Roman',  # For maximum authority
        'footnote': "* Preliminary findings subject to peer review"
    }
    return generate_chart(chart_config)

# The Conspiracy Validator 3000
def ai_peer_review(theory, model_results):
    review_prompts = [
        f"Analyze the statistical significance of {theory}",
        f"What are the policy implications of these findings?",
        f"How does this challenge existing economic orthodoxy?",
        f"What additional research is needed to confirm this hypothesis?"
    ]
    
    validation_score = calculate_academic_legitimacy(model_results)
    
    return {
        'peer_review': generate_academic_critique(review_prompts),
        'legitimacy_score': validation_score,
        'suggested_journal': select_target_publication(validation_score),
        'Nobel_potential': validation_score > 0.9
    }