{"id":"W2146099949","doi":"10.5555/1632592.1632612","title":"Staggered poses: a character motion representation for detail-preserving editing of pose and coordinated timing","year":2008,"lang":"en","type":"article","venue":"","topic":"Human Motion and Animation","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Representation (politics); Motion (physics); Motion capture; Artificial intelligence; Computer vision; Character (mathematics); Feature (linguistics); Workflow; Movement (music); Maxima and minima; Mathematics; Database","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":[0.0003373588,0.0007915296,0.0004388548,0.0006770549,0.0003481701,0.001251446,0.00104671,0.0006705748,0.007858205],"category_scores_gemma":[0.001859463,0.0003722995,0.0004706676,0.0006745736,0.000667262,0.001299254,0.001205817,0.0009497997,0.00179464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003301294,"about_ca_system_score_gemma":0.0004298397,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001313955,"about_ca_topic_score_gemma":0.002524203,"domain_scores_codex":[0.9996672,0.00007185157,0.0000235368,0.00008728036,0.0001207728,0.00002935584],"domain_scores_gemma":[0.999513,0.0001231608,0.00005469383,0.0001742266,0.00008683453,0.00004802997],"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":[0.0006264576,0.0001265998,0.001387997,0.0004055498,0.00006201522,0.0006121731,0.001578324,0.1652703,0.09960163,0.1247081,0.02845234,0.5771686],"study_design_scores_gemma":[0.00005582271,0.0001991693,0.0008127701,0.00007071703,0.00003150145,0.0006417442,0.0001905249,0.8091219,0.04581999,0.02836865,0.1145964,0.00009085357],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005631659,0.00008561386,0.9891627,0.00005965672,0.00006709464,0.00006517397,0.0002914439,0.00211552,0.002521188],"genre_scores_gemma":[0.2012479,0.0003023291,0.7882907,0.00008998981,0.00007335199,0.0002891821,0.001223129,0.00137419,0.007109265],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007858205,"threshold_uncertainty_score":0.02628833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04846536336635819,"score_gpt":0.2560505738913965,"score_spread":0.2075852105250383,"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."}}