{"id":"W2460797105","doi":"10.1145/2897824.2925896","title":"Physics-driven pattern adjustment for direct 3D garment editing","year":2016,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":109,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Point (geometry); Replicate; Computer graphics (images); Space (punctuation); Engineering drawing; Scheme (mathematics); Reuse; Human–computer interaction; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006878365,0.0001570301,0.0001577247,0.0001075828,0.0001273246,0.00001551674,0.0001462593,0.00006183255,0.00003795063],"category_scores_gemma":[0.00000673847,0.0001228191,0.0002195466,0.0001584326,0.00002102749,0.00007555806,0.000002064332,0.00009726704,0.00002039873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005126362,"about_ca_system_score_gemma":0.000005661622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000827343,"about_ca_topic_score_gemma":0.00003222678,"domain_scores_codex":[0.9992266,0.00001195162,0.0001751878,0.0001953444,0.0001506512,0.0002402511],"domain_scores_gemma":[0.9993933,0.0001314733,0.00002284269,0.0003425707,0.00004497155,0.00006485263],"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":[0.000007203528,0.0001299963,0.0001162403,0.00007302642,0.0004529784,0.000001124063,0.0002036628,0.2049099,0.001989449,0.00003552342,0.0005247783,0.7915561],"study_design_scores_gemma":[0.00229915,0.0003130486,0.0004083699,0.0005717929,0.0008623769,0.000003066231,0.0001563297,0.9546371,0.03034285,0.00329653,0.006029825,0.001079565],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005681515,0.00006679737,0.9927472,0.0004071401,0.0004167615,0.0001260686,0.0001220326,0.0002976549,0.000134772],"genre_scores_gemma":[0.9965867,0.0003803455,0.002399176,0.0001165104,0.0002350213,0.0001303637,0.000008686583,0.0000416789,0.0001015491],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9909052,"threshold_uncertainty_score":0.5008416,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02029829926719824,"score_gpt":0.2315582452451204,"score_spread":0.2112599459779221,"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."}}