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Algorithmic targeting and the precision-recall tradeoff 1
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MASS
AI-powered social simulation platform.
cli/ ├── cli.ts # CLI entry (commander) └── commands/ # Commands by domain ├── cohort/ # create, list, delete ├── persona/ # create, list, delete ├── report/ # generate, list, show, delete ├── workspace/ # list, delete, rename, fork ├── chat.ts # Chat with persona └── prompts.ts # Interactive prompts (select, input)
core/ ├── tasks/ # Background task controller (report/persona flows) ├── database/ # DB client (JSON store implementation) ├── helpers/ # Utility functions ├── llm/ # LLM routing, providers, models, schemas ├── storage/ # JSON store paths ├── types/ # Shared types ├── reports/ # Report generation (functions, llm, types) ├── personas/ # Personas and cohorts (controllers, functions, llm, data) ├── workflows/ # Workflow engine, modules (used by report/chat) └── workspace/ # Workspace (conversation state, messages)
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Iyer, G., Yao, Y. (Jesse), & Zhong, Z. (Zachary). (2026). Algorithmic targeting and the precision-recall tradeoff. Marketing Science, mksc.2024.930. https://doi.org/10.1287/mksc.2024.0930 ↩