{"id":"W4388819180","doi":"10.1073/pnas.2306275120","title":"Machine-guided discovery of a real-world rogue wave model","year":2023,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Ocean Waves and Remote Sensing","field":"Earth and Planetary Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"U.S. Army Corps of Engineers; California Department of Parks and Recreation","keywords":"Machine learning; Artificial intelligence; Computer science; Artificial neural network; Context (archaeology); Field (mathematics); Process (computing); Black box; Deep learning; Symbolic regression","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001586774,0.0004236812,0.0004876465,0.0009552935,0.0004363918,0.0008528198,0.00084789,0.0007180643,0.001286001],"category_scores_gemma":[0.009891617,0.0002861003,0.0005617017,0.0005047801,0.001263029,0.001791288,0.0008706428,0.001373113,0.0001799427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008076251,"about_ca_system_score_gemma":0.000934922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003908883,"about_ca_topic_score_gemma":0.004799064,"domain_scores_codex":[0.9997041,0.0001172643,0.00001698397,0.00006775969,0.00005845854,0.00003531799],"domain_scores_gemma":[0.9968213,0.002204743,0.0003724616,0.0003282895,0.0002026468,0.0000707038],"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":[0.00003865098,0.00004060354,0.00946232,0.00006014548,0.00004382254,0.0001527944,0.0001245906,0.9358096,0.001617365,0.03676539,0.0007443483,0.01514037],"study_design_scores_gemma":[0.000003369587,0.000005538619,0.0003915814,0.000004957358,0.000003048782,0.00001089982,0.00001122191,0.9858487,0.0002608478,0.01330958,0.0001469456,0.000003396546],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3946334,0.0001861602,0.5989903,0.001904646,0.00003744362,0.00005288424,0.000367309,0.0004762331,0.003351637],"genre_scores_gemma":[0.9633378,0.00009419819,0.03549488,0.00008355267,0.00002005302,0.00003541971,0.0002985577,0.0000316308,0.0006038376],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003908883,"threshold_uncertainty_score":0.008391798,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07040422852840121,"score_gpt":0.2934377072269574,"score_spread":0.2230334786985562,"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."}}