{"id":"W4417347357","doi":"10.48550/arxiv.2506.09042","title":"Cosmos-Drive-Dreams: Scalable Synthetic Driving Data Generation with World Foundation Models","year":2025,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pipeline (software); Suite; Scalability; Domain (mathematical analysis); Downstream (manufacturing); Generalization; Software; Object (grammar); Scale (ratio)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001137724,0.001262047,0.000528038,0.0009106506,0.0004211798,0.0009817231,0.002837096,0.001152187,0.004700275],"category_scores_gemma":[0.005287538,0.0008871364,0.001304151,0.0007520603,0.0005915254,0.001203761,0.001729461,0.00181932,0.002512732],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009445682,"about_ca_system_score_gemma":0.001442965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01602061,"about_ca_topic_score_gemma":0.02984563,"domain_scores_codex":[0.9994868,0.0001145354,0.00002827186,0.0001779231,0.0001477364,0.00004474339],"domain_scores_gemma":[0.9989447,0.0003579961,0.00004716547,0.0003311697,0.0002220192,0.00009705038],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005300593,0.0005278228,0.009103416,0.0005646963,0.0003385732,0.0003299417,0.0002771295,0.6172538,0.007798994,0.007447674,0.2113497,0.1444781],"study_design_scores_gemma":[0.0001041149,0.0000490405,0.0008360536,0.00002462992,0.00001144675,0.00006638079,0.00004772263,0.975222,0.003865595,0.005082452,0.01466358,0.00002698106],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1184113,0.001035135,0.666343,0.001863932,0.00125358,0.0009964786,0.07492775,0.1235226,0.01164623],"genre_scores_gemma":[0.384516,0.0003786254,0.4276818,0.0005651122,0.00009348004,0.001030251,0.1744953,0.007062082,0.00417749],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01602061,"threshold_uncertainty_score":0.03185469,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05412283681051307,"score_gpt":0.252163083235779,"score_spread":0.198040246425266,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}