{"id":"W2245825454","doi":"10.20380/gi2015.28","title":"Twist and pulse: ephemeral adaptation to improve icon selection on smartphones","year":2015,"lang":"en","type":"article","venue":"Canada Human-Computer Communications Society","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Ephemeral key; Icon; Computer science; Adaptation (eye); Distraction; Visual search; Computer vision; Human–computer interaction; Artificial intelligence; Psychology","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":[0.0004128534,0.0006770733,0.0003512167,0.0004470565,0.0001841974,0.0005213706,0.0006314176,0.0003583838,0.003222501],"category_scores_gemma":[0.003712378,0.0002541702,0.0002179859,0.0002552455,0.0002642658,0.0009254845,0.001019669,0.0003731019,0.0003860491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001470148,"about_ca_system_score_gemma":0.0001910788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000531257,"about_ca_topic_score_gemma":0.0009514458,"domain_scores_codex":[0.9997094,0.00007958368,0.00002243346,0.00005912572,0.00007603893,0.0000534402],"domain_scores_gemma":[0.9978471,0.001240504,0.000210703,0.0003013257,0.0002505873,0.000149814],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.002592336,0.0006121054,0.005954756,0.0008039008,0.0000676417,0.0006737816,0.001641897,0.005615307,0.6308366,0.001484686,0.002754844,0.3469622],"study_design_scores_gemma":[0.000664998,0.008951898,0.1098563,0.0003495401,0.0006343428,0.003930291,0.001635152,0.1740771,0.6514239,0.003319984,0.04466293,0.0004936015],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.815354,0.0006289727,0.1733204,0.0001348459,0.00008737198,0.0003024428,0.000171116,0.005124169,0.004876563],"genre_scores_gemma":[0.9138225,0.0002566329,0.08337883,0.0001278487,0.00003243093,0.0001323258,0.00009077317,0.0003146999,0.001843983],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003222501,"threshold_uncertainty_score":0.01078033,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0381634933893606,"score_gpt":0.2814524101521764,"score_spread":0.2432889167628158,"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."}}