{"id":"W4289146976","doi":"10.52591/lxai201812035","title":"ChaLearn AutoML Challenges","year":2018,"lang":"en","type":"article","venue":"","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Conference Board of Canada","funders":"","keywords":"Relevance (law); Computer science; Data science; Artificial intelligence; Machine learning; Engineering ethics; Engineering; Political science","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":[0.01608815,0.001530571,0.001806585,0.003277919,0.003466581,0.01129149,0.005625315,0.005907061,0.04995778],"category_scores_gemma":[0.0353858,0.0009163809,0.001231787,0.003542559,0.004772411,0.01884765,0.01167614,0.008305077,0.07743767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003930961,"about_ca_system_score_gemma":0.008492632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007183143,"about_ca_topic_score_gemma":0.008848849,"domain_scores_codex":[0.9849229,0.00471665,0.000838294,0.002628261,0.005683555,0.001210254],"domain_scores_gemma":[0.9798468,0.00661458,0.0004806288,0.004604738,0.00679923,0.001654001],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001467841,0.00009802711,0.0005184489,0.0004598087,0.00001853466,0.0001476073,0.0002204798,0.001762541,0.0008794626,0.09600978,0.6305683,0.2691702],"study_design_scores_gemma":[0.00004260496,0.00005475491,0.000265094,0.0002176901,0.000007990545,0.0002804828,0.0003392647,0.01773774,0.002171601,0.151956,0.8268765,0.00005030549],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.0109042,0.0184376,0.4024691,0.2036714,0.02053183,0.0007622011,0.01072566,0.06328148,0.2692164],"genre_scores_gemma":[0.100236,0.01478023,0.3701359,0.06245899,0.01251767,0.001806992,0.04918747,0.0204252,0.3684516],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.04995778,"threshold_uncertainty_score":0.1671254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03474226566271634,"score_gpt":0.2753298332905767,"score_spread":0.2405875676278603,"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."}}