{"id":"W4241048887","doi":"10.1145/1731903.1731944","title":"Getting practical with interactive tabletop displays","year":2009,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Affordance; Computer science; Human–computer interaction; Visualization; Multi-touch; Face (sociological concept); Interactive visualization; Information visualization; Data visualization; Multimedia; 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":[0.001469786,0.001247863,0.0004148137,0.0006447085,0.00169133,0.005973369,0.001537412,0.002180061,0.03477393],"category_scores_gemma":[0.01142196,0.000597158,0.0006592511,0.000720114,0.001785294,0.007186394,0.006597277,0.001970218,0.008044763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002850102,"about_ca_system_score_gemma":0.0003518208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003877237,"about_ca_topic_score_gemma":0.0005697561,"domain_scores_codex":[0.9981993,0.0005277412,0.00008894684,0.0002604073,0.0006916199,0.0002321637],"domain_scores_gemma":[0.9962391,0.002073666,0.00011409,0.0009324735,0.0003723633,0.0002683291],"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":[0.0003343274,0.0003661161,0.003437736,0.002524614,0.00007160345,0.003048928,0.0434716,0.00372916,0.1141806,0.1094318,0.09351116,0.6258924],"study_design_scores_gemma":[0.0001023055,0.0004263953,0.006318792,0.0006841819,0.00005224837,0.003798075,0.01406742,0.00557565,0.02650221,0.05435883,0.8879209,0.0001929454],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1065316,0.003923696,0.6364099,0.007508795,0.0006925518,0.000427693,0.0004366743,0.008884547,0.2351846],"genre_scores_gemma":[0.4288938,0.005385644,0.516891,0.001825962,0.0004581156,0.0007030249,0.0006428662,0.00203824,0.04316135],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03477393,"threshold_uncertainty_score":0.1163304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01037285860957599,"score_gpt":0.282971018394398,"score_spread":0.272598159784822,"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."}}