{"id":"W4254624012","doi":"10.1145/503387.503388","title":"Acquisition of expanding targets","year":2002,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Fitts's law; Computer science; Selection (genetic algorithm); Task (project management); Focus (optics); Target acquisition; Human–computer interaction; Artificial intelligence; Engineering; Systems engineering","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":[0.0006288844,0.0006536968,0.0006801751,0.0002767634,0.0002380564,0.0007747341,0.0006425933,0.0005445845,0.004505783],"category_scores_gemma":[0.007794802,0.000467968,0.0002222972,0.0001940308,0.0002559647,0.001476828,0.00158029,0.0006925321,0.001043071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001359947,"about_ca_system_score_gemma":0.0002364321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006050227,"about_ca_topic_score_gemma":0.0004747706,"domain_scores_codex":[0.9995628,0.00006621995,0.00003224233,0.0001149052,0.0001568258,0.00006698354],"domain_scores_gemma":[0.9958651,0.00272674,0.0002892793,0.0004846236,0.0003688401,0.0002653754],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004565305,0.0002259108,0.001907562,0.0002136622,0.00001546465,0.0002166534,0.0008081942,0.001468804,0.8742478,0.00116446,0.0004845462,0.1187903],"study_design_scores_gemma":[0.0001320982,0.005864372,0.0601495,0.0001097974,0.000113985,0.002090821,0.0008839106,0.05245486,0.8629925,0.002111012,0.01297908,0.00011806],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9261089,0.0003033317,0.06383086,0.00007272467,0.00002533968,0.0001741167,0.0001038624,0.001125867,0.008254983],"genre_scores_gemma":[0.9394981,0.0004689343,0.05132257,0.0001360928,0.00002372432,0.0002545164,0.000387331,0.0004322162,0.007476543],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004505783,"threshold_uncertainty_score":0.01507336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01865669958022965,"score_gpt":0.2532912065322731,"score_spread":0.2346345069520435,"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."}}