{"id":"W2158269718","doi":"10.1145/1731903.1731926","title":"Getting practical with interactive tabletop displays","year":2009,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":50,"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); Information 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":[0.002020487,0.001498976,0.0005089852,0.0008850038,0.001432169,0.006189261,0.00208924,0.002690561,0.06906377],"category_scores_gemma":[0.01665527,0.0007779708,0.0007315769,0.000934297,0.001591828,0.00900376,0.006562101,0.002369127,0.02385337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003735158,"about_ca_system_score_gemma":0.0004691272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005037558,"about_ca_topic_score_gemma":0.0006284261,"domain_scores_codex":[0.9971185,0.0006977794,0.0001480059,0.0003596519,0.001379087,0.0002970796],"domain_scores_gemma":[0.9944148,0.002626821,0.0001546724,0.001415833,0.0009367313,0.0004510382],"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":[0.000258403,0.0003005697,0.002073134,0.002558732,0.00006614815,0.001846574,0.01428877,0.002630249,0.07321826,0.09483058,0.1541859,0.6537428],"study_design_scores_gemma":[0.0000748797,0.0002787366,0.003230844,0.0006377063,0.00004186318,0.00193135,0.004432766,0.003493255,0.01540441,0.04696554,0.9233826,0.0001260538],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.03658577,0.005511856,0.6668565,0.007977762,0.001241411,0.0004849371,0.0005200855,0.01532203,0.2654998],"genre_scores_gemma":[0.2678849,0.01182163,0.6219115,0.003397607,0.001276797,0.0009681739,0.001540727,0.004523445,0.08667526],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.06906377,"threshold_uncertainty_score":0.2310413,"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."}}