{"id":"W4246006611","doi":"10.1145/1185657.1185777","title":"Motion doodles","year":2006,"lang":"en","type":"article","venue":"","topic":"Human Motion and Animation","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Sketch; Computer science; Motion (physics); Cursive; Character (mathematics); Set (abstract data type); Process (computing); Character animation; Parsing; Parameterized complexity; Computer graphics (images); Sequence (biology); Motion capture; Artificial intelligence; Animation; Computer vision; Programming language; Computer animation; Algorithm; Mathematics; Geometry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005025134,0.0009496351,0.0005439563,0.0006527512,0.0006375454,0.001161447,0.001470558,0.0008315932,0.05885512],"category_scores_gemma":[0.002443093,0.000450628,0.0004979002,0.0003094226,0.0005224295,0.001859407,0.002514471,0.000836072,0.008306107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003332286,"about_ca_system_score_gemma":0.00037862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007545509,"about_ca_topic_score_gemma":0.001416249,"domain_scores_codex":[0.9995895,0.00005530506,0.00003556479,0.0001401521,0.0001383075,0.00004125037],"domain_scores_gemma":[0.9993973,0.0001854329,0.00003543175,0.0001832456,0.00009101645,0.00010759],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001300298,0.0001952549,0.002021916,0.001770851,0.0000731236,0.0006404513,0.001478285,0.007476479,0.07863238,0.06727169,0.07160208,0.7675372],"study_design_scores_gemma":[0.0002102668,0.0003130069,0.001577685,0.0002303179,0.00004472699,0.001102547,0.0002412708,0.04330294,0.03609614,0.01286662,0.9039187,0.00009581159],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.01811932,0.001189093,0.910094,0.0005800689,0.0008471204,0.000585078,0.002250257,0.01931192,0.04702321],"genre_scores_gemma":[0.2368996,0.002201796,0.6313671,0.0007621545,0.0002411456,0.001218168,0.006403708,0.004746694,0.1161596],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.05885512,"threshold_uncertainty_score":0.19689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004602306622816064,"score_gpt":0.1629542300006218,"score_spread":0.1583519233778057,"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."}}