{"id":"W2070869270","doi":"10.1109/icsc.2013.72","title":"A Customizable Time Warping Method for Motion Alignment","year":2013,"lang":"en","type":"article","venue":"","topic":"Human Motion and Animation","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Dynamic time warping; Computer science; Image warping; Process (computing); Artificial intelligence; Motion (physics); Computer vision; Personalization; Simple (philosophy); Algorithm; Pattern recognition (psychology)","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":[0.0005408889,0.00123732,0.0005535149,0.0007971032,0.0003944551,0.0005427072,0.0009747832,0.0006633869,0.00560262],"category_scores_gemma":[0.001532956,0.000450822,0.00058524,0.00116581,0.0004076621,0.0007928496,0.0008921173,0.001149291,0.00195731],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003234131,"about_ca_system_score_gemma":0.0007538426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001764793,"about_ca_topic_score_gemma":0.002897474,"domain_scores_codex":[0.9994356,0.0000947686,0.00003089552,0.0001369232,0.000269642,0.00003220108],"domain_scores_gemma":[0.9995809,0.0001080114,0.00005484845,0.0001093567,0.0001160065,0.00003087106],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001360476,0.00009616779,0.0004410605,0.000239362,0.0001128296,0.0002523871,0.0001078345,0.08586533,0.1478922,0.01486988,0.008896388,0.7410904],"study_design_scores_gemma":[0.00003448226,0.000143912,0.0009306048,0.0000367275,0.00004273205,0.0008730536,0.00002936928,0.8671189,0.08500572,0.005319282,0.04037691,0.00008820028],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001500021,0.00007989216,0.9967654,0.00001670743,0.0000395588,0.0000327626,0.00003922442,0.0007784997,0.0007479686],"genre_scores_gemma":[0.04024113,0.0002057194,0.954903,0.00005604255,0.00006115015,0.0001447659,0.0003346187,0.000688468,0.003365043],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00560262,"threshold_uncertainty_score":0.01874268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01010475496237036,"score_gpt":0.2302448307415255,"score_spread":0.2201400757791551,"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."}}