{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003161233,0.0002632214,0.0003133665,0.0004650532,0.0002662761,0.0005690384,0.001197231,0.0001105045,0.000001919576],"category_scores_gemma":[0.00001790361,0.0002547116,0.000209195,0.0009074738,0.00004837173,0.0009504108,0.0001523843,0.0001557651,0.00001473537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006301917,"about_ca_system_score_gemma":0.00009756838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004187727,"about_ca_topic_score_gemma":0.000009726227,"domain_scores_codex":[0.9980841,0.00007936853,0.0004215711,0.0006039507,0.0003344519,0.0004765257],"domain_scores_gemma":[0.9983218,0.0001239835,0.000206554,0.0007397516,0.0003692297,0.0002386529],"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":[0.00002235749,0.0003957917,0.0002758905,0.00004333617,0.00005169866,0.00001547354,0.000140067,0.000925212,0.00003913791,0.9696814,0.008876735,0.01953294],"study_design_scores_gemma":[0.0007036153,0.0007851049,0.0004225419,0.00006057776,0.00002365357,0.000009539969,0.00005051701,0.9862915,0.0004818847,0.003062227,0.007788254,0.0003205891],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001207781,0.00001891428,0.9960566,0.0009811897,0.0007675961,0.0002755559,0.00002920974,0.0004845412,0.0001786694],"genre_scores_gemma":[0.9327567,0.000004140938,0.06073433,0.005993537,0.0002329812,0.000009740491,0.0001989289,0.00002158598,0.00004806218],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9853663,"threshold_uncertainty_score":0.9999905,"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."}}