{"id":"W2896357116","doi":"10.1007/978-3-030-01388-2_4","title":"Interaction for Immersive Analytics","year":2018,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":54,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Human–computer interaction; Visual analytics; Analytics; Visualization; Data science; Data visualization; Data exploration; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005379611,0.0003408084,0.0003522378,0.0007979847,0.0002077287,0.0005869302,0.002314338,0.000202156,0.00005759039],"category_scores_gemma":[0.0001424446,0.0003216669,0.0001375978,0.0005293817,0.0004225977,0.0007229616,0.0007694688,0.0002935895,0.00008816621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002455984,"about_ca_system_score_gemma":0.0003492324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004347246,"about_ca_topic_score_gemma":0.00003482759,"domain_scores_codex":[0.9974896,0.00001417251,0.0004236665,0.001087703,0.0005599473,0.0004249355],"domain_scores_gemma":[0.9977022,0.0003252566,0.0003154922,0.0010043,0.0005195151,0.0001332372],"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":[0.00002865535,0.0001271451,0.00004576855,0.0001726866,0.000104334,0.00005641272,0.003035839,0.03056982,0.0003614152,0.2542542,0.004711746,0.706532],"study_design_scores_gemma":[0.0001880914,0.0001790982,0.000005258032,0.0001681394,0.00001360175,0.000017254,4.645513e-7,0.8772221,0.001565793,0.09588159,0.02435864,0.0004000131],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000005338095,0.00004956703,0.9947647,0.0005347984,0.002077651,0.0002759761,0.00001836781,0.00005554025,0.002218055],"genre_scores_gemma":[0.04218023,0.0001298437,0.9409476,0.0087531,0.002610774,0.00001724898,0.0001460545,0.00009766356,0.005117497],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8466523,"threshold_uncertainty_score":0.9999235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03413281021332345,"score_gpt":0.3160419451228415,"score_spread":0.281909134909518,"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."}}