{"id":"W2163656795","doi":"10.1109/iri.2009.5211539","title":"Visual integration tool for heterogeneous data type by unified vectorization","year":2009,"lang":"en","type":"article","venue":"","topic":"Web Data Mining and Analysis","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; Schema (genetic algorithms); Data integration; Vectorization (mathematics); Data mining; Visualization; Data type; Information retrieval; Bin; Algorithm; Programming language","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":[0.001984868,0.001467054,0.001030155,0.005948891,0.0005607987,0.003157594,0.001623398,0.0009025025,0.0206644],"category_scores_gemma":[0.005554324,0.0005977369,0.001383105,0.004029103,0.0005867852,0.004382122,0.003068388,0.001477942,0.004456756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005901257,"about_ca_system_score_gemma":0.0007940585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002427879,"about_ca_topic_score_gemma":0.002026706,"domain_scores_codex":[0.9991892,0.0001750817,0.0001097799,0.0001383726,0.0003158888,0.00007167245],"domain_scores_gemma":[0.9980707,0.0008435781,0.0001297891,0.0003155126,0.0005191821,0.0001212073],"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":[0.0008842803,0.0002097231,0.002366281,0.0009670338,0.0002347339,0.0007398338,0.001614474,0.01597455,0.02968815,0.06038169,0.1065932,0.7803461],"study_design_scores_gemma":[0.0003033521,0.0002013578,0.003112996,0.0003514808,0.0001547692,0.0009934779,0.0009448351,0.6062174,0.03945677,0.1177903,0.230229,0.0002442003],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002032076,0.0001082226,0.965243,0.0001800762,0.00007509107,0.00008575628,0.0009097834,0.02969221,0.00167378],"genre_scores_gemma":[0.04330536,0.0002561171,0.9468755,0.0001726902,0.00005376447,0.0003824971,0.002294211,0.003945251,0.002714665],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0206644,"threshold_uncertainty_score":0.06912929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03482391784012756,"score_gpt":0.3078712463183315,"score_spread":0.2730473284782039,"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."}}