{"id":"W4404986528","doi":"10.48550/arxiv.2411.15499","title":"Asymmetric Errors","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Banff International Research Station for Mathematical Innovation and Discovery; U.S. Department of Energy","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001586536,0.0003579762,0.0004919439,0.00131853,0.0001037669,0.0002692228,0.002011251,0.0004335693,0.0002771756],"category_scores_gemma":[0.001599791,0.0003113568,0.0004195503,0.002917848,0.0001559154,0.0001007856,0.002468769,0.001027008,0.00354867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002442217,"about_ca_system_score_gemma":0.0003032442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005627584,"about_ca_topic_score_gemma":0.00001042337,"domain_scores_codex":[0.9971317,0.0001604382,0.0004284167,0.001529718,0.0003674769,0.0003822438],"domain_scores_gemma":[0.9969058,0.0008929121,0.0001927581,0.001494049,0.0002694587,0.0002450204],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001768604,0.00004311028,0.0003774073,0.00006260299,0.00008747217,0.0005693483,0.00007732246,0.7915472,0.000004352125,0.183288,0.02195374,0.001971811],"study_design_scores_gemma":[0.0001249114,0.00002568291,0.0004359283,0.00007207349,0.00011265,0.000005276134,0.00008944703,0.4023277,0.00001341553,0.5887753,0.007636803,0.0003807107],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1130273,0.001539816,0.8073352,0.0003516848,0.006663312,0.0005882607,0.0001178997,0.0008415094,0.06953504],"genre_scores_gemma":[0.9698817,0.00008233175,0.0007572313,0.00004140456,0.0001587528,8.173438e-7,0.000006760929,0.00003229047,0.02903872],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8568544,"threshold_uncertainty_score":0.9999338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2149656346657044,"score_gpt":0.2494067536634139,"score_spread":0.03444111899770955,"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."}}