{"id":"W2081034291","doi":"10.1145/1322192.1322245","title":"Speech-filtered bubble ray","year":2007,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Cursor (databases); Bubble; Property (philosophy); Ray casting; Computer vision; Point (geometry); Artificial intelligence; Workspace; Speech recognition; Robot; Visualization; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002001737,0.00007124001,0.00006738654,0.00006948411,0.00005286812,0.0000546475,0.000442389,0.00002545947,0.0002714854],"category_scores_gemma":[0.00001844085,0.0000586932,0.00005054958,0.0001647929,0.00001420287,0.0004443568,0.0001124015,0.00006874378,0.0010992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002486969,"about_ca_system_score_gemma":0.00001532349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004426556,"about_ca_topic_score_gemma":0.00001170244,"domain_scores_codex":[0.9993122,0.00001044524,0.0001083567,0.0001929925,0.0001282227,0.0002478232],"domain_scores_gemma":[0.9994901,0.00005600298,0.00002849774,0.0002809773,0.0000823385,0.00006207652],"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":[0.00003122276,0.000160852,0.001161226,0.000006450186,0.0000415856,0.0001885391,0.0008923704,0.000006112015,0.6045162,0.3138422,0.05161276,0.02754045],"study_design_scores_gemma":[0.0003554337,0.0001090397,0.03160195,0.000009141952,0.000002791573,0.00003547702,0.000190516,0.001540286,0.9109292,0.001717774,0.05326922,0.0002391471],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01692468,0.00001113938,0.728295,0.0003076314,0.0003832357,0.00004421759,2.965907e-7,0.00002560375,0.2540082],"genre_scores_gemma":[0.9583895,0.000001513858,0.02900904,0.002348459,0.00007033603,8.872253e-7,0.000001126396,0.000004163156,0.01017503],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9414648,"threshold_uncertainty_score":0.9996786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01374910875500168,"score_gpt":0.268167506971432,"score_spread":0.2544183982164304,"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."}}