{"id":"W1967451046","doi":"10.1145/2449396.2449439","title":"User-adaptive information visualization","year":2013,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":148,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Visualization; Computer science; Human–computer interaction; Information visualization; Visual analytics; Data visualization; Perception; User interface; Artificial intelligence","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":[0.002387071,0.0007792558,0.0006520586,0.0007665239,0.0003079406,0.001804436,0.001292894,0.0008541055,0.002843786],"category_scores_gemma":[0.01473524,0.0003315614,0.0004846021,0.0006065044,0.0003325237,0.002853043,0.001662229,0.0008688805,0.0009588324],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003333461,"about_ca_system_score_gemma":0.0003673366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001101353,"about_ca_topic_score_gemma":0.00162168,"domain_scores_codex":[0.9982442,0.0006991063,0.0001015824,0.0005006731,0.0003562937,0.00009820115],"domain_scores_gemma":[0.9917795,0.004415222,0.0003812172,0.001965804,0.001161425,0.0002968897],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001696723,0.001007083,0.03602235,0.0007162813,0.0004255,0.0002830092,0.003121712,0.02164557,0.09382968,0.005650295,0.0129313,0.8226705],"study_design_scores_gemma":[0.0002989575,0.001882886,0.07409874,0.0002133731,0.0004224849,0.001748742,0.001565245,0.7456876,0.08367622,0.03063308,0.05940749,0.0003652484],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3153616,0.001384183,0.6515372,0.0006837802,0.0001101868,0.00052535,0.0005309955,0.02198659,0.007880111],"genre_scores_gemma":[0.8155054,0.0004594098,0.1795578,0.0001819688,0.00005647494,0.0002284044,0.0005762319,0.0003056846,0.003128707],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002843786,"threshold_uncertainty_score":0.0126242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01589117803304085,"score_gpt":0.2730499844225932,"score_spread":0.2571588063895523,"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."}}