Fix evaluation bias to unlock better models on Amazon Bedrock

Property Finder found that 96.8% of its evaluation labels came directly from its incumbent vision model's predictions rather than human verification, biasing comparisons against alternatives. After building expert-annotated ground truth (356 UAE images) and running evolutionary prompt optimization from v0 to v27, it selected Llama 4 Maverick 17B Instruct on Amazon Bedrock, reaching a Micro F1 of 0.80 versus 0.56 for its previous model on the evaluation set, at an estimated 86% lower cost per 1,000 images.