{"id":"W1971948928","doi":"10.1145/1570433.1570469","title":"The tradeoff between spatial jitter and latency in pointing tasks","year":2009,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":101,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Alphanumeric; Jitter; Computer science; Gesture; Latency (audio); Modality (human–computer interaction); Security token; Human–computer interaction; Low latency (capital markets); Speech recognition; Computer vision; Telecommunications; Computer network","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":[0.007582395,0.001365176,0.001115308,0.001960643,0.0009559764,0.003008927,0.001852978,0.001940209,0.004854401],"category_scores_gemma":[0.05862261,0.0008690962,0.0003697524,0.002063837,0.0008722977,0.004402572,0.001952592,0.001407411,0.002502222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001031314,"about_ca_system_score_gemma":0.002024917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001749449,"about_ca_topic_score_gemma":0.001736915,"domain_scores_codex":[0.9956043,0.001215886,0.0004787144,0.0005907955,0.001450638,0.000659668],"domain_scores_gemma":[0.9341614,0.05143457,0.00319308,0.004062259,0.004677072,0.002471688],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.01314327,0.0008586341,0.0273389,0.001778206,0.0002404172,0.001069394,0.001865839,0.05003526,0.3850257,0.02269654,0.003468979,0.4924788],"study_design_scores_gemma":[0.002149417,0.01187602,0.1545164,0.001058803,0.001725589,0.01643269,0.003421278,0.2427818,0.4379773,0.09637317,0.0307951,0.0008925439],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3868576,0.01106009,0.5789533,0.001551665,0.0006337166,0.000297085,0.0005177718,0.004888021,0.01524081],"genre_scores_gemma":[0.9228891,0.002983967,0.06677608,0.0004086281,0.0003984001,0.0001798067,0.0003839226,0.0009332508,0.005046883],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007582395,"threshold_uncertainty_score":0.04010004,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009467708650837325,"score_gpt":0.2450180392231524,"score_spread":0.2355503305723151,"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."}}