{"id":"W2038402279","doi":"10.1145/1073204.1073287","title":"Multi-finger gestural interaction with 3D volumetric displays","year":2005,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Computer graphics (images); Leverage (statistics); Visualization; 3D interaction; Computer vision; Virtual reality; Volume rendering; Artificial intelligence; Stereo display; Human–computer interaction; Depth perception; Perception","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":[],"consensus_categories":[],"category_scores_codex":[0.0001044723,0.0002444109,0.0001711011,0.0006552614,0.0003624541,0.0001410857,0.00074901,0.00009312412,0.00006931402],"category_scores_gemma":[0.00002888449,0.000204679,0.0001560843,0.001283534,0.00006842701,0.001604946,0.00001528074,0.0005768241,0.0002303577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009798085,"about_ca_system_score_gemma":0.00003700514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007015953,"about_ca_topic_score_gemma":0.0002241665,"domain_scores_codex":[0.9985821,0.00006052502,0.0002224347,0.0004766831,0.0003118981,0.0003463134],"domain_scores_gemma":[0.9985797,0.000214619,0.0001029265,0.0007847163,0.000208675,0.0001093339],"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":[0.002004611,0.01390617,0.01328025,0.0001942544,0.002858732,0.0002659163,0.0185524,0.0416567,0.09466293,0.01950228,0.007933469,0.7851823],"study_design_scores_gemma":[0.007969226,0.00434691,0.2398085,0.0004832368,0.0004894299,0.0008201859,0.001433195,0.5630025,0.09275014,0.0005151084,0.08467535,0.003706272],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03928241,0.00004269581,0.957578,0.001862134,0.0005566861,0.0001789675,0.00000949765,0.00008077366,0.0004088024],"genre_scores_gemma":[0.9429177,0.00006638842,0.05496475,0.001477008,0.00005723725,0.00003818994,0.000006023243,0.0000204652,0.0004522426],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9036353,"threshold_uncertainty_score":0.834657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02312537820302526,"score_gpt":0.2690496624794349,"score_spread":0.2459242842764096,"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."}}