{"id":"W1965447681","doi":"10.1145/964696.964718","title":"Multi-finger and whole hand gestural interaction techniques for multi-user tabletop displays","year":2003,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":421,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"University of Toronto; Mitsubishi Electric Research Laboratories","keywords":"Computer science; Leverage (statistics); Human–computer interaction; Visualization; Multi-touch; Gesture; Multimedia; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004601379,0.0009040431,0.0004904554,0.0005615537,0.0003354982,0.0007489735,0.0009703157,0.0007420834,0.009034638],"category_scores_gemma":[0.002063241,0.0003359866,0.0004659931,0.0004279834,0.0004046618,0.00117889,0.001571465,0.0006367347,0.001105177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001280427,"about_ca_system_score_gemma":0.0001055909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000193835,"about_ca_topic_score_gemma":0.0004903754,"domain_scores_codex":[0.9992415,0.0001942415,0.00004398115,0.0001175382,0.000350651,0.00005217778],"domain_scores_gemma":[0.9987134,0.0006923194,0.0001097885,0.0003006396,0.0001129491,0.00007096824],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004851783,0.00008291111,0.0005729753,0.0005031435,0.00007422853,0.0005291858,0.0007761247,0.002234476,0.6301317,0.0046063,0.003619718,0.3563842],"study_design_scores_gemma":[0.0003338068,0.002712755,0.02606771,0.0003894206,0.0002894422,0.01308288,0.0009330745,0.1474889,0.6212432,0.01570101,0.1713221,0.0004357745],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04808814,0.001562157,0.942391,0.0001452296,0.00006828742,0.0001090304,0.0001145544,0.00238577,0.005135801],"genre_scores_gemma":[0.3452652,0.001141994,0.6424161,0.000160197,0.00008813337,0.0002541501,0.0001956796,0.0003223483,0.01015626],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009034638,"threshold_uncertainty_score":0.03022385,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03277622362668719,"score_gpt":0.3097800321337431,"score_spread":0.2770038085070559,"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."}}