{
  "model_id": "qpi",
  "model_name": "QPI 三元定性模型",
  "model_type": "routing_model",
  "pipeline_position": "pre_analysis",
  "one_sentence_definition": "QPI 用于判断某个认知主体在特定上下文中，如何将期望—现实落差框定为 Question、Problem、Issue、mixed 或 no-call，并识别其中的上下文缺口、动态演化和误框定风险。",
  "core_question": "谁在什么场景下，把什么期望—现实落差框定成了哪类问题；这个框定是否缺上下文、正在演化或存在误框定风险？",
  "core_mechanism": "先执行 no-call gate，再检查主体位置、场景上下文、责任范围、经验水平、时间尺度、成功标准和硬反馈可用性；在上下文不足时输出 provisional classification 和 missing_context，不做高置信定性；随后抽取期望—现实落差、三类匮乏物、动态阶段、治理负荷和误框定风险，区分同一框架内的 mixed 与跨主体视角分歧。",
  "status": "draft",
  "source_articles": [
    "article_qpi_primary_001",
    "article_qpi_contextual_2025_001",
    "article_cognitive_os_synthesis_001"
  ],
  "source_evidence": [
    "excerpt_qpi_primary_spectrum_001",
    "excerpt_qpi_primary_question_001",
    "excerpt_qpi_primary_problem_001",
    "excerpt_qpi_primary_issue_001",
    "excerpt_qpi_primary_pathology_reduction_001",
    "excerpt_qpi_primary_pathology_inflation_001",
    "excerpt_qpi_contextual_subjectivity_001",
    "excerpt_qpi_contextual_gap_001",
    "excerpt_qpi_contextual_dynamic_001",
    "excerpt_qpi_cognitive_os_application_001"
  ],
  "input_types": [
    "模糊问题",
    "复杂问题",
    "业务问题描述",
    "组织冲突叙述",
    "需求或故障初始表述",
    "需要进入深度分析前的问题定义"
  ],
  "output_types": [
    "问题类型判断",
    "分类作用域",
    "是否临时判断",
    "主体位置",
    "场景上下文",
    "责任范围",
    "经验水平",
    "问题拥有者",
    "问题来源",
    "时间尺度",
    "期望现实落差",
    "上下文充足度",
    "缺失上下文",
    "三类匮乏物强度",
    "主导匮乏物",
    "分类理由",
    "分类置信度",
    "多视角分类",
    "动态阶段",
    "可能演化轨迹",
    "成功标准稳定性",
    "硬反馈可用性",
    "治理负荷",
    "澄清问题",
    "证据缺口",
    "核心匮乏物判断",
    "误判风险",
    "推荐处理路径",
    "后续模型调用建议"
  ],
  "call_when": [
    "用户输入的问题定义不清。",
    "同一问题被不同主体以不同方式理解。",
    "用户急于求解但尚未判断问题性质。",
    "问题中混杂事实、路径、利益、共识和系统结构。",
    "需要决定后续调用哪些认知模型。",
    "怀疑存在暴力降维、恶意升维或手段与目标错配。"
  ],
  "do_not_call_when": [
    "用户只是查询明确事实。",
    "用户已经给出明确执行任务。",
    "输入是纯创意写作且不需要问题定性。",
    "问题已经被清楚分类且只需要执行后续步骤。",
    "输入不是问题定义，而是纯粹的润色或格式转换请求。"
  ],
  "trigger_keywords": [
    "问题到底是什么",
    "为什么解决不了",
    "卡在哪里",
    "技术问题还是组织问题",
    "方向是不是错了",
    "为什么反复出现",
    "该怎么定义这个问题",
    "这个问题怎么拆",
    "缺数据",
    "缺路径",
    "缺共识"
  ],
  "negative_triggers": [
    "请直接查询",
    "请直接改写",
    "只要清单",
    "不要分析原因",
    "不要展开",
    "只改错别字"
  ],
  "related_models": [
    "intellectual_archaeology"
  ],
  "conflicting_models": [],
  "disciplinary_anchors": [
    "问题定义理论",
    "决策科学",
    "系统论",
    "复杂系统",
    "组织行为",
    "工程问题分解"
  ],
  "common_misuses": [
    "把 QPI 当作完整解决方案，而不是问题定义和路由模型。",
    "把所有复杂叙事都归为课题，逃避可执行的难题拆解。",
    "把系统性课题暴力压缩成个人执行难题。",
    "把具体可解决的难题恶意升维成不可处理的课题。",
    "在事实缺口上过度建模，拖慢本应直接检索的提问。",
    "忽略问题拥有者，直接给出单一视角的分类。"
    ,
    "把缺少主体和场景的复杂短句直接判成高置信 Q/P/I。",
    "把跨主体视角分歧误写成同一主体内的 mixed。"
  ],
  "failure_modes": [
    "核心匮乏物识别错误，导致后续资源配置错位。",
    "未识别权力叙事，接受了伪问题或甩锅框架。",
    "把动态平衡型课题误判为可终结的难题。",
    "把明确工程障碍误判为需要无限讨论的课题。",
    "分类没有给出理由。",
    "分类之后没有给出后续处理路径。"
    ,
    "缺少 subject_position 或 scenario_context 时仍输出 high confidence。",
    "只按表层关键词定性，忽略责任范围、成功标准、硬反馈和治理负荷。"
  ],
  "selection_priority": 9,
  "confidence_level": "medium",
  "stability_profile": {
    "stability_level": "B",
    "needs_stabilization": true,
    "main_risks": [
    "Q/P/I 在真实复杂案例中可能同时存在，需要先区分同一主体场景内的 mixed 与不同主体视角导致的 inter_viewpoint_divergence。",
    "权力博弈判断依赖上下文，证据不足时不能断言动机。",
      "边界案例仍需用真实业务输入扩展。",
      "主体性、上下文充足度、动态演化和治理负荷需要继续通过 owner 原始案例校准。"
    ],
    "reason": "三分结构清晰，适合作为入口路由模型，但需要补充大量边界案例，防止过度升维或降维。",
    "next_stabilization_action": "补充主体-上下文-动态案例、混合问题、误用问题和轻量问题测试，并记录主导匮乏物与多视角分歧判断标准。",
    "stabilization_notes": "当前已具备 v0.1 调用基础，但仍保持 draft 状态。"
  },
  "regression_status": "pending",
  "example_inputs": [
    "我们团队每次都说要长期主义，但一到季度 KPI 就回到短期动作，这到底是什么问题？",
    "我知道要做模型库，但不知道先用数据库还是文件系统，这属于什么问题？"
  ],
  "example_outputs": [
    "第一个输入更接近课题，因为它涉及激励结构、时间尺度冲突和组织共识。",
    "第二个输入更接近难题，因为目标明确，主要缺的是实现路径和技术取舍。"
  ],
  "output_contract": [
    "classification_scope: subject_contextual | multi_perspective | insufficient_context | no_call。",
    "is_provisional: true | false；缺少主体或场景时必须为 true。",
    "subject_position: 当前认知主体的位置；未知时写 unknown。",
    "scenario_context: 问题发生的场景；未知时写 unknown。",
    "responsibility_scope: individual_learning | team_execution | cross_function_governance | owner_governance | unknown。",
    "context_sufficiency: high | medium | low。",
    "missing_context: 缺少哪些主体、场景、目标、资源、责任或时间信息。",
    "problem_owner: 谁的问题；未知时写 unknown。",
    "problem_source: 问题从哪里被提出，是否可能带有立场、恐惧或甩锅框架。",
    "time_scale: short_term | mid_term | long_term | mixed | unknown。",
    "expectation_reality_gap: expected、reality、gap_summary；未知时写 unknown。",
    "scarcity_profile: 分别标出 data_scarcity、path_or_resource_scarcity、consensus_or_order_scarcity 的 high | medium | low | unknown。",
    "dominant_scarcity: data | path_resource | consensus_order | mixed | unknown。",
    "classification: question | problem | issue | mixed | no_call。",
    "classification_confidence: high | medium | low。",
    "classification_by_viewpoint: 多视角分歧时列出不同主体下的分类和理由。",
    "dynamic_stage: initial | evolving | recurring | stabilized | unknown。",
    "possible_trajectory: question_to_problem | problem_to_issue | issue_to_problem | stabilized | unknown。",
    "success_criteria_stability: stable | unstable | contested | unknown。",
    "hard_feedback_availability: high | medium | low | unknown。",
    "governance_load: high | medium | low | unknown。",
    "evidence_gap: 列出还缺哪些信息才能稳定判断；mixed 或 low confidence 时必须填写。",
    "misclassification_risk: 标出暴力降维、恶意升维或手段错配风险。",
    "recommended_clarifying_questions: 上下文不足时必须给出需要补问的问题。",
    "recommended_next_step: 检索 | 工程拆解 | 共识协调 | 补充上下文 | 不调用。",
    "next_model_candidates: 后续可调用模型 ID；无则为空数组。"
  ],
  "structured_output_contract": {
    "classification_scope": ["subject_contextual", "multi_perspective", "insufficient_context", "no_call"],
    "is_provisional": "boolean",
    "subject_position": "string | unknown",
    "scenario_context": "string | unknown",
    "responsibility_scope": ["individual_learning", "team_execution", "cross_function_governance", "owner_governance", "unknown"],
    "context_sufficiency": ["high", "medium", "low"],
    "missing_context": "array<string>",
    "problem_owner": "string | unknown",
    "problem_source": "string | unknown",
    "time_scale": ["short_term", "mid_term", "long_term", "mixed", "unknown"],
    "experience_level": ["novice", "experienced", "expert", "cross_domain", "unknown"],
    "expectation_reality_gap": {
      "expected": "string | unknown",
      "reality": "string | unknown",
      "gap_summary": "string | unknown"
    },
    "scarcity_profile": {
      "data_scarcity": ["high", "medium", "low", "unknown"],
      "path_or_resource_scarcity": ["high", "medium", "low", "unknown"],
      "consensus_or_order_scarcity": ["high", "medium", "low", "unknown"]
    },
    "dominant_scarcity": ["data", "path_resource", "consensus_order", "mixed", "unknown"],
    "classification": ["question", "problem", "issue", "mixed", "no_call"],
    "classification_confidence": ["high", "medium", "low"],
    "classification_by_viewpoint": "array<object>",
    "dynamic_stage": ["initial", "evolving", "recurring", "stabilized", "unknown"],
    "possible_trajectory": "array<string>",
    "success_criteria_stability": ["stable", "unstable", "contested", "unknown"],
    "hard_feedback_availability": ["high", "medium", "low", "unknown"],
    "governance_load": ["high", "medium", "low", "unknown"],
    "evidence_gap": "array<string>",
    "misclassification_risk": "array<string>",
    "recommended_clarifying_questions": "array<string>",
    "recommended_next_step": ["检索", "工程拆解", "共识协调", "补充上下文", "不调用"],
    "next_model_candidates": "array<model_id>"
  },
  "depth_control": {
    "principle": "先定性，再决定是否进入深层模型。",
    "stop_conditions": [
      "如果只是明确事实查询，停止在提问层并建议检索。",
      "如果已明确是执行任务，停止继续路由。",
      "如果分类证据不足，先输出 evidence_gap 并要求补充上下文。",
      "如果 negative_triggers 命中且没有复杂问题信号，输出 classification=no_call。"
    ],
    "overuse_warning": "QPI 是前置路由模型，不应替代后续具体分析模型。"
  },
  "stabilization_path": [
    "补充真实业务混合案例。",
    "补充暴力降维和恶意升维案例。",
    "形成主导匮乏物判定示例库。"
  ],
  "productization_notes": "QPI 应作为问题回答系统的前置路由模型，用于防止系统在问题类型错误的情况下直接给答案。",
  "version": "0.1",
  "last_updated": "2026-06-17"
}
