Todoo Nada Inc., a PR tech company headquartered in Taito-ku, Tokyo (President and CEO: Yasuyuki Matsumoto, hereinafter "the Company"), has conducted the first large-scale quantitative survey on how many of Japan's major 3,166 media outlets can pass through the pretraining data pipeline of generative AI (LLM), using the LLM-Friendly Check feature built into its PR effectiveness measurement service, "Qlipper." The results revealed that only 10.0% (317 outlets) of domestic media are expected to be included in LLM pretraining data, and even when including those with "conditional passage," the figure reaches only 33.6% (1,063 outlets). For the first time, a two-tiered structure was quantitatively confirmed: traditional media (national newspapers, regional newspapers, and news agencies) are completely blocked via robots.txt, while major portals and online news sites are excluded due to content structure issues. Additionally, it was revealed that about 30% of press release distribution services (wire services)—long relied upon by PR professionals—are classified as "immediately discarded," despite having fully open robots.txt files, exposing the structural barriers of distribution sites to LLM reach. ■ Survey Background: What Is the LLM Pretraining Data Pipeline? Generative AIs such as ChatGPT, Claude, and Gemini acquire language capabilities by learning from vast amounts of text on the web. However, not all web content is used for training. AI vendors generally use a multi-stage filtering pipeline to select training data: Stage Content Reasons for Rejection 1 Crawl Permission Check (robots.txt layer) Check the site's robots.txt to see if AI crawlers are allowed. robots.txt is a "gentlemen's agreement" and not legally binding Blocked by robots.txt for specific crawlers 2 Content Retrieval (UA check/WAF layer) Crawlers send actual requests to websites. Servers, CDNs, or WAFs decide whether to respond based on User-Agent strings AI crawlers rejected by UA check (returns 403/