{"id":"W4250556463","doi":"10.1145/958206.958207","title":"Using cursor prediction to smooth telepointer jitter","year":2003,"lang":"en","type":"article","venue":"","topic":"Evacuation and Crowd Dynamics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Jitter; Computer science; Immediacy; Cursor (databases); Naturalness; Testbed; Human–computer interaction; Artificial intelligence; Computer vision","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":[0.001085545,0.001093778,0.0007216024,0.000415659,0.0003424158,0.0007388382,0.001093603,0.0007553782,0.001355644],"category_scores_gemma":[0.01301614,0.0003472455,0.0002168447,0.0003094908,0.000417068,0.001234446,0.0006791726,0.0007964874,0.0004502937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003232657,"about_ca_system_score_gemma":0.0005514712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002467897,"about_ca_topic_score_gemma":0.001851978,"domain_scores_codex":[0.999292,0.0002152698,0.00005300138,0.0002079472,0.0001564619,0.00007527026],"domain_scores_gemma":[0.9934849,0.004059937,0.0006407073,0.0009528084,0.0006336688,0.0002280292],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.004055267,0.0008520014,0.01942141,0.000526067,0.00009762838,0.0003885324,0.001705147,0.1680202,0.1864776,0.001787074,0.001653971,0.6150151],"study_design_scores_gemma":[0.000295875,0.002705325,0.02136362,0.0000814404,0.000160897,0.0006025435,0.0003025355,0.8212535,0.1460509,0.003015931,0.003992116,0.0001752928],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5754875,0.0003121537,0.4157467,0.0001982025,0.0001004584,0.0001385665,0.0001044847,0.005383084,0.002528977],"genre_scores_gemma":[0.9505524,0.0000890123,0.04840932,0.00002780104,0.00001557908,0.00004066211,0.00006187498,0.00008216731,0.0007212703],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002467897,"threshold_uncertainty_score":0.005741,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0204705360305583,"score_gpt":0.2441839592590942,"score_spread":0.2237134232285359,"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."}}