{"id":"W2920848790","doi":"10.1007/978-3-030-29135-8_8","title":"AutoML @ NeurIPS 2018 Challenge: Design and Results","year":2019,"lang":"en","type":"book-chapter","venue":"The Springer series on challenges in machine learning","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Acadia University","funders":"Microsoft Research","keywords":"Lifelong learning; Competition (biology); Computer science; Duration (music); Artificial intelligence; Autonomous learning; Data science; Machine learning; Mathematics education; Psychology; Pedagogy","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":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.002852026,0.0008586816,0.0007661487,0.0004995837,0.0004254907,0.0003302085,0.001866541,0.0005585775,0.00002915144],"category_scores_gemma":[0.0002202616,0.0007088091,0.0001390761,0.0001069883,0.0002074388,0.0004860098,0.001144096,0.003519504,0.0003796769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001197479,"about_ca_system_score_gemma":0.0001168362,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003997791,"about_ca_topic_score_gemma":0.0002492449,"domain_scores_codex":[0.9952746,0.0006262711,0.0009010526,0.00181883,0.0007406593,0.0006386085],"domain_scores_gemma":[0.9955693,0.001123137,0.0008220712,0.002250642,0.00008539369,0.0001493797],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003619913,0.00007591734,0.0000422193,0.0003097072,0.0001120399,0.0001037804,0.003827945,0.006653282,0.00001196445,0.5242,0.0004160179,0.4638851],"study_design_scores_gemma":[0.001015933,0.001176133,0.001239102,0.0005758003,0.00003243284,0.00007710435,0.00008344626,0.09593384,0.000004762909,0.00878297,0.8899816,0.001096909],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00007240787,0.04359129,0.02354107,0.05835682,0.002649041,0.002190566,0.00004151583,0.001909979,0.8676473],"genre_scores_gemma":[0.137165,0.171053,0.0213028,0.000916287,0.001380841,0.0001718378,0.0002420853,0.0006752462,0.6670929],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.8895655,"threshold_uncertainty_score":0.9995363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05760360569810447,"score_gpt":0.2601444043592527,"score_spread":0.2025407986611483,"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."}}