{"id":"W2057047210","doi":"10.1145/1870076.1870077","title":"Modeling locomotor control","year":2011,"lang":"en","type":"article","venue":"ACM Transactions on Applied Perception","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Engineering and Physical Sciences Research Council","keywords":"Gaze; Computer science; Control (management); Artificial intelligence; Visual control; Computer vision; Human–computer interaction","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":[0.0002358651,0.0006372902,0.0005454703,0.0004709427,0.0004252678,0.000979424,0.0009778324,0.001031778,0.005348038],"category_scores_gemma":[0.001096378,0.0003366146,0.0005604426,0.0003437892,0.0007834164,0.00082156,0.0008962644,0.0006807382,0.0009659505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007269685,"about_ca_system_score_gemma":0.0006167567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01376342,"about_ca_topic_score_gemma":0.007898981,"domain_scores_codex":[0.9998503,0.00002946416,0.000008263297,0.00005065172,0.00004132532,0.00002005862],"domain_scores_gemma":[0.9997941,0.00007057261,0.00004356627,0.0000194677,0.00005411986,0.00001822768],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004064083,0.00001999726,0.0008995755,0.000107585,0.00003658657,0.0001057574,0.0001596725,0.919497,0.003146032,0.0600979,0.001487403,0.01440179],"study_design_scores_gemma":[0.00001078938,0.0000272492,0.0002831293,0.00001524907,0.000009788658,0.00002394993,0.00001778866,0.9811544,0.0002222148,0.01433092,0.003896116,0.000008437079],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04364294,0.002010114,0.9124568,0.0009061889,0.0002356811,0.00009233691,0.0007323266,0.0007005057,0.03922302],"genre_scores_gemma":[0.9173626,0.00192017,0.04972984,0.0002249677,0.0001366656,0.0004493956,0.0007351077,0.0001838641,0.02925739],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01376342,"threshold_uncertainty_score":0.02736664,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03883479809623689,"score_gpt":0.2374088126794607,"score_spread":0.1985740145832238,"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."}}