188 lines
7.5 KiB
JSON
188 lines
7.5 KiB
JSON
{
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"model_id": "intellectual_archaeology",
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"model_name": "思想考古学",
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"model_type": "deep_modeling_model",
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"pipeline_position": "deep_analysis",
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"one_sentence_definition": "思想考古学是一种从表层应用逐层下钻到哲学基岩的建模方法，用于发现支撑一个模型或判断的深层假设、核心机理和动态韧性来源。",
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"core_question": "当前问题、方案或模型背后，隐藏了哪些更深层的结构性假设？",
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"core_mechanism": "把待建模对象放入七层深度框架：应用层、领域层、过程层、目的层、核心机理层、人类能力层、哲学基岩层；逐层追问支撑上一层的假设，并以最小充分下潜原则停止，避免为了深刻而深刻。",
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"status": "draft",
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"source_articles": [
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"article_intellectual_archaeology_primary_001",
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"article_cognitive_os_synthesis_001"
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],
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"source_evidence": [
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"excerpt_ia_primary_definition_001",
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"excerpt_ia_primary_layers_001",
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"excerpt_ia_primary_resilience_001",
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"excerpt_ia_cognitive_os_minimum_depth_001",
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"excerpt_ia_primary_validation_001"
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],
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"input_types": [
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"复杂问题",
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"系统性议题",
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"反复失败的问题",
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"专家隐性知识",
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"认知模型草稿",
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"产品底层逻辑",
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"需要抽取底层假设的业务方案"
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],
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"output_types": [
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"层级化问题地图",
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"是否应该调用",
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"进入思想考古的理由",
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"建议最大下潜层级",
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"实际分析层级",
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"停止理由",
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"不继续下潜理由",
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"深层假设清单",
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"最小充分下潜层级",
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"模型稳固性判断",
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"需要验证的薄弱环节",
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"后续建模建议"
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],
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"call_when": [
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"QPI 判断问题偏课题或中重型难题。",
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"问题具有高复用价值。",
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"用户希望从文章中抽取模型。",
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"当前解释停留在表层工具或症状。",
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"需要把专家隐性知识显性化。",
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"需要为一个模型寻找更稳固的底层结构。",
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"一个问题反复解决但反复失败。"
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],
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"do_not_call_when": [
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"当前只是缺少一个事实或材料位置，直接检索即可。",
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"问题属于低风险轻量表达，不值得进入深层建模。",
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"继续下钻不再改变判断、路径、验证方式或行动边界。",
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"用户明确只需要短平快执行，不需要模型化解释。",
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"缺少足够领域材料，无法区分真实底层假设和空泛哲学化表达。"
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],
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"trigger_keywords": [
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"深层结构",
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"底层逻辑",
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"模型稳不稳",
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"为什么反复失败",
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"问题的根在哪里",
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"沉淀成模型",
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"从文章抽取模型",
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"方法论的基岩",
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"隐性知识",
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"哲学基岩"
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],
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"negative_triggers": [
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"快速回答",
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"不要展开",
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"只查事实",
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"只要执行步骤",
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"不要深入分析",
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"只改文案"
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],
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"related_models": [
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"qpi"
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],
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"conflicting_models": [
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"fast_execution_flow"
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],
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"disciplinary_anchors": [
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"哲学",
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"认识论",
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"系统论",
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"复杂系统",
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"认知心理学",
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"专家知识显性化",
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"因果推理",
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"设计理论"
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],
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"common_misuses": [
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"把思想考古学误用为文章摘要或概念堆叠。",
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"为了显得深刻而无限下钻。",
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"把所有轻量问题都拖入七层分析。",
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"只做纵向下潜而缺少横向模型竞争。",
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"用哲学基岩替代现实验证。",
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"下潜后没有回到可行动结论。"
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],
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"failure_modes": [
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"分析很深但不能改变判断或行动。",
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"层级之间没有清楚递进关系。",
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"把所有问题都下钻到哲学层。",
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"输出只有抽象概念而没有模型结构。",
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"没有说明应该在哪一层停止。",
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"没有指出需要证据验证的地方。"
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],
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"selection_priority": 7,
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"confidence_level": "medium",
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"stability_profile": {
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"stability_level": "B",
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"needs_stabilization": true,
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"main_risks": [
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"七层结构需要进一步稳定。",
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"容易过度下潜。",
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"容易输出抽象概念而缺少行动回路。",
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"需要更多真实案例验证。"
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],
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"reason": "纵向下潜机制清晰，适合深度建模，但七层结构和停止条件需要进一步稳定。",
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"next_stabilization_action": "补充不同复杂度问题的下潜深度测试，明确最小充分下潜原则。",
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"stabilization_notes": "当前适合作为中重型问题的 draft 深度建模模块。"
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},
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"regression_status": "pending",
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"example_inputs": [
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"我想把过去文章中的认知模型抽取出来，但不知道这些模型到底稳不稳，应该怎么判断？",
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"现代人为什么一边渴望连接，一边又渴望逃离连接？"
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],
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"example_outputs": [
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"第一个输入适合下潜到核心机理层，判断文章、模型卡、系统调用、回归测试之间的关系。",
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"第二个输入可从应用层、评价层、过程层、目的层和人类能力层分析连接与逃离连接的双重机制。"
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],
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"output_contract": [
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"should_call: true | false。",
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"entry_reason: 为什么值得进入思想考古；不应调用时说明 no-call 原因。",
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"recommended_max_depth: application | domain | process | purpose | core_mechanism | human_capability | philosophical_bedrock。",
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"layers_to_analyze: 实际需要分析的层级数组。",
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"stop_reason: 为什么停在这一层。",
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"no_deeper_reason: 继续下潜不会改变什么。",
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"assumptions_by_layer: 按七层列出关键假设；未分析层级保留空数组。",
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"validation_needed: 哪些判断需要现实反馈、数据、专家盲审或红队。",
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"action_implication: 下潜结果如何改变下一步行动。"
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],
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"structured_output_contract": {
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"should_call": "boolean",
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"entry_reason": "string",
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"recommended_max_depth": ["application", "domain", "process", "purpose", "core_mechanism", "human_capability", "philosophical_bedrock"],
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"layers_to_analyze": "array<layer_id>",
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"stop_reason": "string",
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"no_deeper_reason": "string",
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"assumptions_by_layer": {
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"application": "array<string>",
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"domain": "array<string>",
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"process": "array<string>",
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"purpose": "array<string>",
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"core_mechanism": "array<string>",
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"human_capability": "array<string>",
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"philosophical_bedrock": "array<string>"
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},
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"validation_needed": "array<string>",
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"action_implication": "string"
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},
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"depth_control": {
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"principle": "最小充分下潜",
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"stop_conditions": [
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"已经足以改变决策。",
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"继续下潜不会增加解释力。",
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"缺少证据支撑更深推断。",
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"问题不值得重型建模。",
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"用户当前只需要执行层结果。",
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"QPI 未放行中重型难题或课题时，不进入完整思想考古。",
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"如果 recommended_max_depth 低于 philosophical_bedrock，不得自动展开到哲学基岩。"
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],
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"overuse_warning": "思想考古不是所有问题的默认流程，必须先经过问题价值评估和 QPI 定性。"
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},
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"stabilization_path": [
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"补充轻量、中量、重量问题的边界测试。",
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"补充不同领域的七层下钻案例。",
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"建立停止条件和现实验证的示例库。"
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],
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"productization_notes": "思想考古适合作为中重度问题的深层建模模块，不应默认全量调用。它应该由 QPI、问题复杂度和复用价值共同触发。",
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"version": "0.1",
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"last_updated": "2026-06-16"
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}
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