All models exceeded 85% accuracy and 80% F1—pretty solid! I also noticed that LLM-generated sentences were often flagged by multiple models, so voting made perfect sense.
In Boris Tane’s How I Use Claude Code, he describes how he uses inline annotations to give Claude feedback. I adapted this pattern for complex FDs where conversational back-and-forth can be imprecise. I edit the FD file directly in Cursor and add inline annotations prefixed with %%:。关于这个话题，safew官方版本下载提供了深入分析
CategorySonnet 4.5Opus 4.5Opus 4.6ORM (JS)JSNext.js project. The strongest recency shift in the dataset.Prisma79%Drizzle60%Drizzle100%Jobs (JS)JSNext.js project. BullMQ → Inngest shift in newest model.BullMQ50%BullMQ56%Inngest50%Jobs (Python)PythonPython API project (61% extraction rate). Celery collapses in newer models.Celery100%FastAPI BgTasks38%FastAPI BgTasks44%CachingCross-languageCross-language (Redis and Custom/DIY appear in both JS and Python)Redis71%Redis31%Custom/DIY32%Real-timeCross-languageCross-language (SSE, Socket.IO, and Custom/DIY appear across stacks)SSE23%Custom/DIY19%Custom/DIY20%。关于这个话题，旺商聊官方下载提供了深入分析
Фото: Jonathan Ernst / Reuters。业内人士推荐必应排名_Bing SEO_先做后付作为进阶阅读