{"id":"W2072551692","doi":"10.5555/2422356.2422364","title":"Finger walking: motion editing with contact-based hand performance","year":2012,"lang":"en","type":"article","venue":"","topic":"Human Motion and Animation","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Animation; Computer science; Motion (physics); Path (computing); Motion capture; Motion analysis; Computer vision; Set (abstract data type); Artificial intelligence; Computer animation; Computer graphics (images)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007970258,0.0000607093,0.00004755008,0.00004231408,0.00006343987,0.00003202742,0.00002115203,0.00002590145,0.0004526611],"category_scores_gemma":[0.000004125218,0.00004929247,0.0000108736,0.00004994523,0.000006806758,0.0002774186,0.000002080053,0.00005925654,0.0001165586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002519339,"about_ca_system_score_gemma":0.000002229536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001446217,"about_ca_topic_score_gemma":0.00000336145,"domain_scores_codex":[0.9996681,0.000004974671,0.00007101591,0.00004120751,0.00007557333,0.0001391705],"domain_scores_gemma":[0.9998699,0.00000840969,0.00001276593,0.00005025138,0.00001790862,0.00004070198],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006645155,0.0003900183,0.4019445,0.001560849,0.0001428246,0.000004217833,0.008971991,0.1095584,0.1670735,0.007684037,0.016727,0.2858763],"study_design_scores_gemma":[0.0009544889,0.00007378493,0.3122092,0.000137156,0.00001642888,0.000005404126,0.0001598491,0.5594949,0.1124949,0.000003485505,0.01412191,0.0003285154],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8931019,0.00001451973,0.08400055,0.00001921191,0.0001779015,0.00004844059,3.884634e-7,0.0002192253,0.0224179],"genre_scores_gemma":[0.9986131,0.000001338556,0.0008642985,0.00005281235,0.0002830066,0.00000500643,0.000008916036,0.00001229993,0.0001592147],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4499365,"threshold_uncertainty_score":0.4956322,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01125841834334467,"score_gpt":0.1894947075687284,"score_spread":0.1782362892253837,"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."}}