{"id":"W2090977515","doi":"10.1007/s00371-007-0141-8","title":"Motion learning-based framework for unarticulated shape animation","year":2007,"lang":"en","type":"article","venue":"The Visual Computer","topic":"Human Motion and Animation","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Polygon mesh; Embedding; Animation; Computer science; Motion (physics); Space (punctuation); Point (geometry); Key (lock); Computer graphics; Computer animation; Computer graphics (images); Function (biology); Artificial intelligence; Computer vision; Algorithm; Mathematics; Geometry","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":[0.000297074,0.00007665047,0.00006230681,0.00005352119,0.000107932,0.00004580947,0.00005280114,0.00005920628,0.00007835417],"category_scores_gemma":[0.00001634186,0.00006133557,0.00004303525,0.0001171804,0.00001243583,0.00006034515,0.000006513044,0.0001190243,0.00008769355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003119164,"about_ca_system_score_gemma":0.000002374568,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.642837e-7,"about_ca_topic_score_gemma":9.701337e-7,"domain_scores_codex":[0.9995276,0.00002181928,0.000144306,0.00007655129,0.00008828873,0.0001414719],"domain_scores_gemma":[0.9997264,0.0001154497,0.00002644529,0.00006113671,0.00004193367,0.00002860324],"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":[0.00005450153,0.00009221385,0.0003210349,0.0001226132,0.00004188005,0.000001345061,0.001138169,0.8366587,0.007515348,0.01828689,0.001052979,0.1347143],"study_design_scores_gemma":[0.0001810745,0.00008722431,0.0127054,0.00002290937,0.000006708127,6.002492e-7,0.000009576012,0.9827228,0.002231185,0.000836778,0.001117985,0.00007775621],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3514904,0.000005995606,0.6478704,0.00006106887,0.0001375969,0.0001138403,2.99629e-7,0.0002708983,0.00004949866],"genre_scores_gemma":[0.9904084,4.750759e-7,0.009085506,0.000153593,0.0002844741,0.000004899019,0.00002586976,0.00001868823,0.00001813572],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6389179,"threshold_uncertainty_score":0.2501192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01798293072493367,"score_gpt":0.2840968433601749,"score_spread":0.2661139126352412,"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."}}