{"id":"W2073996339","doi":"10.1145/2702123.2702300","title":"How Much Faster is Fast Enough?","year":2015,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":86,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Latency (audio); Computer science; Perception; Tapping; Lag; Variety (cybernetics); Human–computer interaction; Task (project management); Artificial intelligence; Psychology; Engineering; Telecommunications; Operating system","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":[0.002775779,0.000516594,0.0004599416,0.0004025917,0.0004510887,0.002611855,0.0004324303,0.00101904,0.003623326],"category_scores_gemma":[0.05436658,0.0002213508,0.0002272411,0.0004410507,0.0006592645,0.003965796,0.0005952122,0.0007452044,0.0005988597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003667514,"about_ca_system_score_gemma":0.0003610269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008162285,"about_ca_topic_score_gemma":0.0007005499,"domain_scores_codex":[0.9978573,0.0009271617,0.0001808406,0.0004478604,0.0004334961,0.0001534277],"domain_scores_gemma":[0.9498652,0.04283515,0.002986974,0.001239852,0.002269631,0.0008032564],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0094495,0.001007757,0.1970865,0.005023032,0.0004625857,0.0005748715,0.018842,0.003180368,0.1552915,0.009943385,0.007698623,0.5914398],"study_design_scores_gemma":[0.0009526087,0.0168004,0.5780896,0.001995668,0.002548892,0.004078547,0.0564041,0.03982998,0.1553657,0.05474374,0.08775768,0.001433008],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9559044,0.003025189,0.02650952,0.001246589,0.0002714659,0.0001735766,0.0002782813,0.0004634976,0.01212755],"genre_scores_gemma":[0.9873302,0.0009783824,0.0101496,0.0003771583,0.00006021399,0.00008410809,0.0001000132,0.0001046009,0.0008157959],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003623326,"threshold_uncertainty_score":0.01467985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0349495674168694,"score_gpt":0.258346595296869,"score_spread":0.2233970278799996,"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."}}