{"id":"W2059082950","doi":"10.1145/1631272.1631467","title":"Interacting with a personal cubic 3D display","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 British Columbia","funders":"","keywords":"Stylus; Computer science; Computer graphics (images); Human–computer interaction; 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":[0.0001933049,0.0003889986,0.0002780702,0.0002246842,0.0005255217,0.0007063067,0.0007021279,0.0004849096,0.02042124],"category_scores_gemma":[0.00075161,0.0002475732,0.0005477909,0.0003060583,0.0003466443,0.0004362884,0.001777034,0.00058501,0.002006147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000278276,"about_ca_system_score_gemma":0.0005210579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004970959,"about_ca_topic_score_gemma":0.007384247,"domain_scores_codex":[0.9997376,0.00003508632,0.000007610951,0.00003126325,0.0001299033,0.00005854659],"domain_scores_gemma":[0.9995696,0.0001228946,0.00002242519,0.00008952343,0.00008970461,0.0001058165],"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":[0.001192547,0.0002613766,0.006883316,0.0006201176,0.00009939279,0.004161677,0.004586285,0.01221016,0.7051259,0.0110248,0.04076387,0.2130706],"study_design_scores_gemma":[0.0003980967,0.001852684,0.03444442,0.0001951378,0.000289309,0.01134403,0.002212666,0.1776782,0.2807772,0.004527473,0.4856481,0.0006326392],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4067923,0.0005143698,0.496502,0.001023499,0.0003795634,0.0004044244,0.001511924,0.01204287,0.08082893],"genre_scores_gemma":[0.7518031,0.000338644,0.2152226,0.0004290789,0.00006673652,0.0001654216,0.0007684503,0.0006235795,0.0305823],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02042124,"threshold_uncertainty_score":0.06831586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00813311177754878,"score_gpt":0.2466628267746013,"score_spread":0.2385297149970525,"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."}}