{"id":"W2403494083","doi":"","title":"Interactive Dimensionality Reduction for Visual Analytics","year":2014,"lang":"en","type":"article","venue":"Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B))","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Dimensionality reduction; Visualization; Visual analytics; Data visualization; Focus (optics); Reduction (mathematics); Metric (unit); Interactive visual analysis; Curse of dimensionality; Analytics; Variable (mathematics); Data mining; Human–computer interaction; Machine learning; Mathematics","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","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0006924181,0.0006244928,0.0007155082,0.0009384403,0.001818641,0.00184404,0.002745673,0.0003213321,0.00007950574],"category_scores_gemma":[0.000304357,0.0006289175,0.0004183873,0.001882361,0.0006444741,0.002702908,0.003574875,0.0004377115,0.00004002435],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001231576,"about_ca_system_score_gemma":0.0003450222,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002774333,"about_ca_topic_score_gemma":0.00003635086,"domain_scores_codex":[0.9965723,0.0003731349,0.0004039545,0.001150866,0.0005624003,0.0009373188],"domain_scores_gemma":[0.996545,0.0007903721,0.0004782301,0.0009120788,0.0005243629,0.0007500139],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00184569,0.0002635945,0.001229282,0.00009859858,0.000411335,0.0001340278,0.02803474,0.001243142,0.000192901,0.9465702,0.006889347,0.01308721],"study_design_scores_gemma":[0.006780102,0.0006444181,0.004325778,0.0001887881,0.0004775178,0.0003272611,0.004464692,0.1900099,0.001393175,0.02295128,0.766717,0.001720182],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1653249,0.0001580138,0.7660211,0.0144496,0.0004796891,0.001354159,0.0004235857,0.000718146,0.05107074],"genre_scores_gemma":[0.9751955,0.0001780087,0.004460384,0.002269835,0.0001909146,0.000006911085,0.0004458914,0.00007674492,0.01717578],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9236189,"threshold_uncertainty_score":0.9996162,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01352812769843497,"score_gpt":0.2404366688615127,"score_spread":0.2269085411630777,"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."}}