{"id":"W4206124320","doi":"10.1109/bigdata52589.2021.9671894","title":"Towards Automated Variability-Aware Machine-Learning-Based Modeling Analysis","year":2021,"lang":"en","type":"article","venue":"2021 IEEE International Conference on Big Data (Big Data)","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Automation; Variety (cybernetics); Data science; Process (computing); Software engineering; Feature (linguistics); Data modeling; Machine learning; Data mining; Artificial intelligence; Engineering","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":[0.01262671,0.001774592,0.002139071,0.003645381,0.001119719,0.006144169,0.004153633,0.001577373,0.001205494],"category_scores_gemma":[0.03603241,0.001404138,0.003784244,0.002793032,0.002024066,0.005493204,0.00569254,0.005116593,0.0009619013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002306542,"about_ca_system_score_gemma":0.005139682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005059343,"about_ca_topic_score_gemma":0.007407763,"domain_scores_codex":[0.9857839,0.005473396,0.001052484,0.001586496,0.005583341,0.0005204456],"domain_scores_gemma":[0.9603447,0.02074512,0.002913669,0.01060356,0.004892696,0.000500162],"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":[0.0001315508,0.0003749538,0.007923882,0.0003890948,0.0003670289,0.0005258311,0.0009420958,0.651414,0.01013773,0.0764772,0.005183101,0.2461336],"study_design_scores_gemma":[0.000006661675,0.00001060508,0.0002365778,0.00002922852,0.00001539668,0.00003772692,0.00004046262,0.9500799,0.002531414,0.04472695,0.002268553,0.00001637631],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002362396,0.00006359869,0.9947984,0.0001998013,0.000007610107,0.00003394056,0.0001000167,0.002153863,0.0002803789],"genre_scores_gemma":[0.1043828,0.0001802857,0.8930463,0.0001863917,0.00004467447,0.0001439319,0.0009577278,0.0007244744,0.0003335377],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01262671,"threshold_uncertainty_score":0.06677723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5463838428580676,"score_gpt":0.4465904440958107,"score_spread":0.0997933987622569,"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."}}