{"id":"W2406643723","doi":"10.14236/ewic/eva2013.6","title":"EMVIZ (flow): An Artistic Tool for Visualising Movement Quality","year":2013,"lang":"en","type":"article","venue":"Electronic workshops in computing","topic":"Human Motion and Animation","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Movement (music); Visualization; Embodied cognition; Human–computer interaction; Artificial intelligence; Dance; 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":[0.001182168,0.001258285,0.0004370392,0.002800795,0.00057138,0.002449018,0.001216725,0.001098784,0.03682198],"category_scores_gemma":[0.005314367,0.0005238346,0.001085809,0.0009975823,0.0008759061,0.002202412,0.003032962,0.001522603,0.004228986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000498041,"about_ca_system_score_gemma":0.000458186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001582142,"about_ca_topic_score_gemma":0.002077781,"domain_scores_codex":[0.9997086,0.00007246143,0.00001705423,0.00005201517,0.000101334,0.00004859294],"domain_scores_gemma":[0.99902,0.0005697574,0.00004716287,0.0001255423,0.0001510152,0.00008652609],"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":[0.001361611,0.0002115353,0.003392624,0.002027108,0.0001254234,0.0007979103,0.005702334,0.02528058,0.06988853,0.08295918,0.1319315,0.6763216],"study_design_scores_gemma":[0.000500395,0.0005008351,0.01044893,0.0009260194,0.0001435184,0.00168707,0.001446152,0.2973484,0.07063061,0.08577147,0.5302251,0.000371472],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01349166,0.0003984699,0.9262147,0.0005265023,0.0003412554,0.0004311568,0.002940483,0.03005485,0.02560093],"genre_scores_gemma":[0.1727811,0.000623036,0.7902443,0.0004820714,0.0001480278,0.001064358,0.003241402,0.01014264,0.02127306],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03682198,"threshold_uncertainty_score":0.1231818,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01640407391507525,"score_gpt":0.2934542462245873,"score_spread":0.277050172309512,"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."}}