{"id":"W4402722158","doi":"10.1145/3670947.3671658","title":"RightSizing: Disentangling Generative Models of Human Body Shapes with Metric Constraints","year":2024,"lang":"en","type":"article","venue":"Graphics Interface","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; University of British Columbia","funders":"","keywords":"Metric (unit); Computer science; Generative grammar; Generative model; Artificial intelligence; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001211988,0.0001849841,0.0002445171,0.0004817915,0.00006581892,0.0000738505,0.0001496687,0.00006544734,0.00003942668],"category_scores_gemma":[0.000004613476,0.0001453009,0.0001188712,0.0007661035,0.0001307401,0.0001412119,0.00002276221,0.0002500805,0.000005470441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002913157,"about_ca_system_score_gemma":0.00001328883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001432431,"about_ca_topic_score_gemma":0.0000277718,"domain_scores_codex":[0.999104,0.00001829258,0.0002573523,0.0002321808,0.0001989109,0.0001892406],"domain_scores_gemma":[0.9996542,0.00005273621,0.00002483926,0.000141289,0.00006812748,0.00005882565],"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":[0.000005110574,0.00002952171,0.00009965837,0.0002256837,0.0009005127,0.00003236367,0.001621448,0.9486498,0.01334162,0.03419751,0.0001408768,0.0007559559],"study_design_scores_gemma":[0.00009454836,0.00004459525,0.000003855097,0.0002492101,0.0001337428,0.000006351901,0.0002147546,0.9680108,0.02539788,0.00563339,0.00002369868,0.0001871749],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3664348,0.003624503,0.6266088,0.00002479223,0.00009337375,0.00006330979,0.00002901976,0.0003052765,0.002816155],"genre_scores_gemma":[0.9987356,0.0001279786,0.0009515276,0.000007478694,0.00004090479,0.000006363126,0.000007347691,0.00003846104,0.00008434181],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6323008,"threshold_uncertainty_score":0.5925201,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02417366752378686,"score_gpt":0.2637390182138716,"score_spread":0.2395653506900848,"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."}}