{"id":"W4294237904","doi":"10.1145/3558774","title":"AutoML Loss Landscapes","year":2022,"lang":"en","type":"article","venue":"ACM Transactions on Evolutionary Learning and Optimization","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Oracle (Canada); University of British Columbia","funders":"","keywords":"Computer science; Machine learning; Artificial intelligence; Set (abstract data type); Convexity; Bayesian probability; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.000255902,0.000110711,0.00008981292,0.0002207962,0.001575696,0.00007295084,0.0003409279,0.00003798072,0.0002421211],"category_scores_gemma":[0.00005944307,0.0001208517,0.00003857689,0.0004785162,0.00002536305,0.0003669528,0.00004092736,0.0004578744,0.00001758845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007609163,"about_ca_system_score_gemma":0.00005225373,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002302691,"about_ca_topic_score_gemma":0.000001402657,"domain_scores_codex":[0.9987604,0.0002732067,0.0001579118,0.0003693434,0.0002779271,0.000161233],"domain_scores_gemma":[0.9993355,0.0001487235,0.00008320537,0.0003280418,0.00004351637,0.00006105239],"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":[0.00001515565,0.00007490767,0.0007088503,0.000004128099,0.000009434048,0.000002015196,0.0002050571,0.9571798,0.00000987456,0.001847067,0.0001068811,0.03983682],"study_design_scores_gemma":[0.0002952391,0.0001877446,0.002308685,0.000004662425,0.000009063186,0.00006695333,0.0001156131,0.961547,0.000004702531,0.0003427049,0.03497006,0.0001475341],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001014819,0.0001845131,0.9939319,0.00359508,0.0001893459,0.00008586857,0.000008674211,0.0004589892,0.0005307753],"genre_scores_gemma":[0.8560658,0.0002118499,0.1416086,0.0001386573,0.00002813091,0.00007276235,0.0001372413,0.00001374117,0.001723302],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8550509,"threshold_uncertainty_score":0.9997241,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008214584684334612,"score_gpt":0.2314862547169162,"score_spread":0.2232716700325816,"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."}}