{"id":"W2170426794","doi":"10.1145/1056808.1056968","title":"Measuring the effective parameters of steering motions","year":2005,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Cursor (databases); Computer science; Path (computing); Simulation; Fitts's law; Motion (physics); Artificial intelligence; 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":[0.001471596,0.0007644828,0.0004482265,0.001240905,0.0002650614,0.001229854,0.0007416257,0.0007863441,0.002024207],"category_scores_gemma":[0.01623565,0.000599489,0.0002986322,0.0009777346,0.0005155821,0.003020994,0.0007142179,0.0007505006,0.0008142867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003493453,"about_ca_system_score_gemma":0.0005097735,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008956169,"about_ca_topic_score_gemma":0.0009353342,"domain_scores_codex":[0.9983028,0.0004640956,0.00009949361,0.0004078088,0.0006392638,0.00008646282],"domain_scores_gemma":[0.9930976,0.003641238,0.0006338907,0.001306722,0.001145565,0.000175078],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005787289,0.0003324855,0.0524025,0.0005570805,0.0003298289,0.0001868435,0.001531543,0.2062504,0.311366,0.02779185,0.002282651,0.3963901],"study_design_scores_gemma":[0.00006688458,0.0006380942,0.06430245,0.00009489802,0.0001276675,0.001014837,0.0004002645,0.7178764,0.1841763,0.02422075,0.006737961,0.0003435268],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1989937,0.0001521605,0.7972972,0.0000389647,0.000016126,0.00008438082,0.0003757748,0.0007102542,0.002331472],"genre_scores_gemma":[0.8972134,0.0001709864,0.1012084,0.00002285947,0.000009147377,0.0001105811,0.0003930701,0.0001999188,0.0006715886],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002024207,"threshold_uncertainty_score":0.007782638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02091910432105588,"score_gpt":0.2421245273939381,"score_spread":0.2212054230728822,"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."}}