{"id":"W2969853078","doi":"10.1007/s11761-019-00272-y","title":"Data mining service recommendation based on dataset features","year":2019,"lang":"en","type":"article","venue":"Service Oriented Computing and Applications","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Data mining; Service (business); Data science; Information retrieval; Business","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":[0.0005981563,0.0008620979,0.001156043,0.006320878,0.0006492721,0.001456026,0.0007758777,0.0007590515,0.001794045],"category_scores_gemma":[0.004608194,0.0001829007,0.001301262,0.007257196,0.0001763987,0.001445827,0.0004487864,0.0008073919,0.001327991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007047327,"about_ca_system_score_gemma":0.0013394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01106034,"about_ca_topic_score_gemma":0.02397522,"domain_scores_codex":[0.9988101,0.00008647046,0.0001403466,0.0002382131,0.0005898418,0.0001350854],"domain_scores_gemma":[0.9978122,0.0006184521,0.0002026019,0.0002787214,0.0008978672,0.0001902659],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001712933,0.001311411,0.4081368,0.00097626,0.001035617,0.000853413,0.0001892516,0.01431453,0.02149764,0.002314969,0.04391929,0.5037379],"study_design_scores_gemma":[0.0001946226,0.0007578968,0.1614836,0.0002813037,0.001301366,0.001919224,0.001202857,0.7705768,0.0278734,0.007908594,0.02637977,0.0001205275],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8328148,0.003680473,0.1102777,0.002075399,0.0006224676,0.0008340215,0.03567776,0.004784054,0.009233376],"genre_scores_gemma":[0.9045799,0.001050541,0.06041103,0.000163289,0.0002319782,0.0001989858,0.03057963,0.0000995273,0.002685028],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01106034,"threshold_uncertainty_score":0.02199191,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02455588047636383,"score_gpt":0.2950804601787307,"score_spread":0.2705245797023669,"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."}}