{"id":"W3048683209","doi":"10.1145/3386569.3392477","title":"Computational design of skintight clothing","year":2020,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Embedding; Computer science; Clothing; Set (abstract data type); Body shape; Nonlinear system; Algorithm; Mathematical optimization; Artificial intelligence; Mathematics; Physics","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":[0.0003492704,0.000486144,0.000555544,0.0005082188,0.0003075762,0.0008781027,0.0008527219,0.000802921,0.002768014],"category_scores_gemma":[0.001074095,0.0005381926,0.000729194,0.0002553463,0.0007261421,0.0006066712,0.001115772,0.0005332449,0.0004541416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004159698,"about_ca_system_score_gemma":0.0006921745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001321414,"about_ca_topic_score_gemma":0.001809692,"domain_scores_codex":[0.9997689,0.00005699271,0.000009322403,0.00003877924,0.00009951551,0.00002655265],"domain_scores_gemma":[0.9997277,0.0001130939,0.00003091357,0.00005338484,0.00004300574,0.00003193877],"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":[0.00001501371,0.00001888782,0.000336747,0.00004650267,0.0000118596,0.00007304805,0.00003760277,0.9746391,0.005653403,0.009549513,0.0003509024,0.009267461],"study_design_scores_gemma":[0.00000286003,0.00000806256,0.00005793937,0.000003557543,0.000001511533,0.00001386295,0.000005765944,0.9958067,0.000502562,0.003031057,0.0005637653,0.000002339113],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03321468,0.00008033344,0.9602523,0.0001347034,0.00003442324,0.00004533013,0.00007435994,0.0002478478,0.005915919],"genre_scores_gemma":[0.5939376,0.0002052406,0.3991658,0.0001243949,0.00002590151,0.0001904928,0.0001654041,0.0002967998,0.005888404],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002768014,"threshold_uncertainty_score":0.009259939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03503944623025766,"score_gpt":0.2272332062864954,"score_spread":0.1921937600562378,"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."}}