{"id":"W2912630731","doi":"10.1145/3300178","title":"Effects of Aging on Small Target Selection with Touch Input","year":2019,"lang":"en","type":"article","venue":"ACM Transactions on Accessible Computing","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; AGE-WELL","keywords":"Touchscreen; Slipping; Computer science; Selection (genetic algorithm); Slip (aerodynamics); Cognition; Contrast (vision); Artificial intelligence; Psychology; Human–computer interaction; Mathematics; Engineering; Neuroscience","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0001146724,0.0002067233,0.0002367997,0.00034407,0.0002156256,0.0001127992,0.0008378588,0.00006075597,0.00003075462],"category_scores_gemma":[0.00001989238,0.000179427,0.00009660834,0.0007812128,0.0000205285,0.0005795918,0.00003161883,0.000366991,0.00007077551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007793204,"about_ca_system_score_gemma":0.00006521918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005437155,"about_ca_topic_score_gemma":0.000005495532,"domain_scores_codex":[0.9986434,0.00008329006,0.0002322809,0.000474715,0.0002481723,0.0003181483],"domain_scores_gemma":[0.9986253,0.0005047591,0.0001824745,0.0004578338,0.0001715931,0.00005799853],"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":[0.0006072947,0.002770745,0.02388288,0.001575399,0.0008834929,0.00005764328,0.00584572,0.3264527,0.4010393,0.007783411,0.0002355124,0.2288659],"study_design_scores_gemma":[0.0009525272,0.0008686191,0.01488286,0.0005890604,0.00002232442,0.00001411886,0.00007025706,0.06084497,0.9210786,0.0002758678,0.000105195,0.0002956241],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3398498,0.0000124173,0.6581391,0.0001287147,0.0003730321,0.0002085215,6.142276e-7,0.00004822777,0.001239592],"genre_scores_gemma":[0.969797,0.00000421909,0.02950978,0.0004524685,0.00003844183,0.000007402403,0.000001476706,0.00001807906,0.0001711436],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6299471,"threshold_uncertainty_score":0.7316822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009789397113984213,"score_gpt":0.251978706665366,"score_spread":0.2421893095513818,"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."}}