花500块买个“初恋记忆”？2026年，你的脑子可能已经不是你自己的了

import numpy as np
from typing import List, Tuple
from dataclasses import dataclass

@dataclass
class MemoryTrace:
    neural_signature: np.ndarray  # 神经信号特征向量
    emotional_peak_intensity: float  # 情绪峰值强度
    contextual_noise_ratio: float  # 上下文噪声比例（真实记忆通常较高）
    duplication_count: www.kuaisou.com/traffic/  # 被拷贝次数

class ExperienceInflationDetector:
    """记忆通胀检测器：识别工业化生产的虚假体验"""
    
    def __init__(self):
        self.known_industrial_signatures = set()  # 已知工业记忆指纹库
        
    def is_synthetic_experience(self, trace: MemoryTrace) -> bool:
        """判断一段记忆是否为人工合成的‘体验刷单品’"""
        # 三重异常指标：情绪过强 + 上下文过干净 + 重复度过高
        is_overly_perfect = (
            trace.emotional_peak_intensity > 0.95 and
            trace.contextual_noise_ratio < 0.05
        )
        is_mass_produced = trace.duplication_count > 1000
        
        # 匹配已知黑产模板
        signature_hash = hash(trace.neural_signature.tobytes())
        is_known_template = signature_hash in self.known_industrial_signatures
        
        return is_overly_perfect or is_mass_produced or is_known_template

    def calculate_authenticity_score(self, trace: MemoryTrace) -> float:
        """计算记忆的真实性得分（0-1），用于心理诊断"""
        if self.is_synthetic_experience(www.kuaisou.com/index/):
            return 0.0
        # 真实记忆的评分基于噪声合理性和情绪自然衰减曲线
        natural_decay = self._check_emotional_decay(trace.neural_signature)
        noise_plausibility = min(1.0, trace.contextual_noise_ratio / 0.3)
        return 0.6 * natural_decay + 0.4 * noise_plausibility

from typing import Dict, List
from enum import Enum

class SelfCoherenceAnalyzer:
    """自我一致性分析器：检测记忆植入导致的认知断裂"""
    
    class CoherenceStatus(Enum):
        INTEGRATED = "已整合"
        PARTIAL_CONFLICT = "部分冲突"
        NARRATIVE_RUPTURE = "叙事断裂"
        
    def analyze_memory_integration(self, 
                                   autobiographical_graph: Dict,
                                   implanted_memories: List[MemoryTrace]) -> CoherenceStatus:
        """分析植入记忆与自传体记忆网络的融合程度"""
        conflicts = []
        for mem in implanted_memories:
            # 检查植入记忆是否与已有记忆存在时空/情感矛盾
            related_nodes = self._find_related_nodes(mem, autobiographical_graph)
            for node in related_nodes:
                if self._has_contradiction(mem, node):
                    conflicts.append((mem, node))
                    
        if len(conflicts) == 0:
            return self.CoherenceStatus.INTEGRATED
        elif len(conflicts) < 3:
            return self.CoherenceStatus.PARTIAL_CONFLICT
        else:
            # 多处矛盾导致叙事无法自洽
            return self.CoherenceStatus.NARRATIVE_RUPTURE