{"id":"W3005749067","doi":"10.5753/sibgrapi.est.2020.12991","title":"Preprocessing Profiling Model for Visual Analytics","year":2020,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Government of Canada","keywords":"Computer science; Preprocessor; Visual analytics; Visualization; Data pre-processing; Profiling (computer programming); Data visualization; Data science; Data mining; Raw data; Analytics; Process (computing); Scope (computer science); Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.006038531,0.001596243,0.0006681099,0.003330671,0.00119974,0.00684263,0.002965294,0.001954554,0.008263783],"category_scores_gemma":[0.02136874,0.0009350427,0.00200774,0.003162252,0.002372212,0.01014015,0.003940682,0.003818853,0.005262956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002249807,"about_ca_system_score_gemma":0.003122357,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003767598,"about_ca_topic_score_gemma":0.003237291,"domain_scores_codex":[0.9937428,0.00237068,0.000541674,0.001263486,0.001607398,0.0004739488],"domain_scores_gemma":[0.9867502,0.004571662,0.000943851,0.004125104,0.003027048,0.0005821464],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004630598,0.000351671,0.004572501,0.000758637,0.0001127643,0.0004027871,0.004238731,0.02672562,0.01353185,0.6528847,0.0351914,0.2607664],"study_design_scores_gemma":[0.00006970923,0.0001566869,0.002031037,0.0005247294,0.00008878909,0.000551783,0.001050669,0.2981152,0.01515395,0.4916563,0.1904493,0.0001519199],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002192493,0.0001442446,0.9852749,0.001243716,0.00006689483,0.0003744429,0.0004952348,0.003837046,0.006371011],"genre_scores_gemma":[0.1079553,0.000480219,0.8806721,0.0009254442,0.0001179103,0.001122687,0.001970998,0.00115276,0.005602589],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008263783,"threshold_uncertainty_score":0.03193521,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09200503410435676,"score_gpt":0.3606945119934958,"score_spread":0.268689477889139,"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."}}