{"id":"W2767200584","doi":"","title":"Touchscreen Accuracy and Usability for Older Adults: A Comparison of Target Selection Methods","year":2017,"lang":"en","type":"book","venue":"The Atrium (University of Guelph)","topic":"Ergonomics and Musculoskeletal Disorders","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Guelph","keywords":"Touchscreen; Usability; Human–computer interaction; Computer science; Selection (genetic algorithm); Psychology; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006484631,0.000537514,0.0006753081,0.001321078,0.0003316224,0.001327568,0.0003316888,0.000533252,0.001326338],"category_scores_gemma":[0.03315996,0.0002425101,0.001299995,0.0007326049,0.0002859143,0.001181501,0.0008525362,0.0003654574,0.0003944963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003579968,"about_ca_system_score_gemma":0.0004180337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002350601,"about_ca_topic_score_gemma":0.003499342,"domain_scores_codex":[0.9955201,0.001206393,0.0007163428,0.0003439977,0.002076559,0.000136578],"domain_scores_gemma":[0.9722537,0.01770112,0.003686843,0.0008600929,0.004892776,0.0006054396],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005345183,0.0005692836,0.7471875,0.002055241,0.0008810498,0.0002263388,0.008114628,0.0003270364,0.003882758,0.0002171239,0.001383484,0.2298104],"study_design_scores_gemma":[0.000122334,0.004591994,0.9858662,0.0003895247,0.0004037689,0.0007372731,0.002640542,0.00165156,0.001328159,0.0002020105,0.001996763,0.00006972633],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9907129,0.003922979,0.001830566,0.0001165854,0.0000489082,0.0001780374,0.0002783105,0.00005075938,0.002861025],"genre_scores_gemma":[0.9927951,0.002212809,0.003434143,0.00008963912,0.00003741118,0.0001778983,0.0003392926,0.00002363712,0.00089016],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006484631,"threshold_uncertainty_score":0.03429443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02880772816424204,"score_gpt":0.3329407984961614,"score_spread":0.3041330703319193,"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."}}