{"id":"W2025394193","doi":"10.1111/j.1467-8659.2009.01475.x","title":"iPCA: An Interactive System for PCA‐based Visual Analytics","year":2009,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":222,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Interactivity; Principal component analysis; Visual analytics; Dimensionality reduction; Human–computer interaction; Visualization; Set (abstract data type); Interface (matter); Interactive visual analysis; User interface; Data mining; Component (thermodynamics); Machine learning; Artificial intelligence; Multimedia","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":[0.002510084,0.001344925,0.0007096714,0.002449407,0.0005856798,0.001812271,0.002075,0.001093765,0.05584106],"category_scores_gemma":[0.007807278,0.0006428368,0.0007397139,0.00116772,0.0004266558,0.001741576,0.003011865,0.001289751,0.008715816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003743821,"about_ca_system_score_gemma":0.000818665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001295558,"about_ca_topic_score_gemma":0.001127503,"domain_scores_codex":[0.9990471,0.0002724345,0.00005915359,0.0001996605,0.0003574911,0.00006403981],"domain_scores_gemma":[0.9934996,0.00408937,0.0002263858,0.0008653766,0.0008309834,0.0004884247],"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":[0.003959215,0.00101386,0.006741358,0.001595353,0.0003239413,0.001707882,0.003038083,0.009012914,0.08696226,0.008739053,0.3236261,0.55328],"study_design_scores_gemma":[0.001757451,0.001260851,0.02450417,0.0005772079,0.0002932703,0.002622448,0.0007117316,0.5267976,0.07274599,0.0218335,0.3461789,0.0007168779],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02313215,0.0002194364,0.5633129,0.0004148709,0.0001498089,0.0007333557,0.00661198,0.3970608,0.008364629],"genre_scores_gemma":[0.2268453,0.0003845242,0.7276353,0.000602166,0.0002557678,0.003694804,0.01102756,0.01992503,0.009629471],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05584106,"threshold_uncertainty_score":0.186807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02419862311286216,"score_gpt":0.3157650869119379,"score_spread":0.2915664637990757,"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."}}