{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002027986,0.0007641886,0.000447107,0.0006322014,0.0003199058,0.0006559342,0.0002579914,0.0004422286,0.002826303],"category_scores_gemma":[0.01720067,0.0001998008,0.0004092843,0.0002831819,0.0003810277,0.0008544917,0.0009712179,0.0004072539,0.0003348246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001820492,"about_ca_system_score_gemma":0.0001935925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002255722,"about_ca_topic_score_gemma":0.002792909,"domain_scores_codex":[0.9990466,0.0001979386,0.0002008194,0.000190315,0.0002627319,0.000101576],"domain_scores_gemma":[0.987597,0.006231125,0.002995463,0.0008683437,0.001722963,0.0005850882],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.007357903,0.0008550266,0.7540308,0.0007065738,0.0003312441,0.003050167,0.006920731,0.001178034,0.10163,0.0002856332,0.0008746921,0.1227793],"study_design_scores_gemma":[0.00002326493,0.003388328,0.9810627,0.00007333048,0.0002433782,0.001324968,0.0008509353,0.001033458,0.01062933,0.0002020318,0.001136163,0.00003213507],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996523,0.0008142901,0.001253634,0.00005112922,0.00003479558,0.00002616715,0.0001327806,0.0000318523,0.001132359],"genre_scores_gemma":[0.9975873,0.0003279624,0.001179917,0.0000531023,0.00001852654,0.00002460213,0.0001174303,0.00002145783,0.0006696283],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002826303,"threshold_uncertainty_score":0.01072514,"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."}}