{"id":"W2040842605","doi":"10.1145/1174429.1174467","title":"An interface for virtual 3D sculpting via physical proxy","year":2006,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":83,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Gesture; Smoothing; Interface (matter); Human–computer interaction; Computer graphics (images); Frame (networking); Virtual reality; Virtual space; Set (abstract data type); Computer vision","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":[0.0004449874,0.0007717119,0.0004148065,0.0003338372,0.0002730812,0.001302748,0.001104315,0.0008125706,0.01481332],"category_scores_gemma":[0.001594001,0.000295506,0.000484491,0.0002249727,0.0005347686,0.001505341,0.002109737,0.0004501003,0.001705789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001355536,"about_ca_system_score_gemma":0.0001783534,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003158712,"about_ca_topic_score_gemma":0.0003312496,"domain_scores_codex":[0.9997048,0.00008563771,0.00002127361,0.00004123408,0.0001181189,0.00002884266],"domain_scores_gemma":[0.9994185,0.0002796903,0.00003060123,0.00014189,0.00004949962,0.00007992365],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001500122,0.0003397781,0.002314915,0.00116932,0.00008228027,0.002855211,0.003882769,0.01150493,0.443406,0.07027566,0.02101289,0.4416562],"study_design_scores_gemma":[0.0004415385,0.001994379,0.005146852,0.000412107,0.0002161464,0.009085502,0.001109371,0.2823108,0.2362012,0.02079641,0.4419095,0.00037628],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04428905,0.0004243393,0.9281723,0.0001837853,0.0001128794,0.0001653226,0.000221838,0.01336679,0.01306364],"genre_scores_gemma":[0.4545324,0.0006049443,0.5203645,0.0002423188,0.00005119789,0.0003009377,0.0004301998,0.00105513,0.02241833],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01481332,"threshold_uncertainty_score":0.04955554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00801451994729081,"score_gpt":0.2842221373793914,"score_spread":0.2762076174321006,"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."}}