{"id":"W2154332168","doi":"10.4271/2004-01-2188","title":"Exploring the Space of Human Body Shapes: Data-driven Synthesis under Anthropometric Control","year":2004,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; University of Washington; Microsoft Research; National Science Foundation","keywords":"Anthropometry; Computer science; Human body; Space (punctuation); Control (management); Computer vision; Artificial intelligence; Geography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007405255,0.000756378,0.001227974,0.0005008483,0.0004957377,0.0001140548,0.00217336,0.0004114332,0.0002582867],"category_scores_gemma":[0.0007383366,0.0005696542,0.0005332858,0.001837653,0.0009959189,0.0007017967,0.0004400482,0.001174006,0.00008155256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003146017,"about_ca_system_score_gemma":0.00006232891,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001624258,"about_ca_topic_score_gemma":0.01901951,"domain_scores_codex":[0.9957553,0.0001201733,0.001173009,0.001025656,0.00101956,0.0009062995],"domain_scores_gemma":[0.9963078,0.0008147585,0.0001896591,0.002297661,0.0001078002,0.0002822685],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00004935565,0.0003120609,0.0000428458,0.00008365954,0.0003017199,0.00002358007,0.00003432569,0.03301814,0.9580216,0.005917046,0.0004741075,0.001721557],"study_design_scores_gemma":[0.001914145,0.001242321,0.9823703,0.0009736192,0.001296024,0.00006838072,0.0008634783,0.00007632359,0.001775997,0.003154954,0.004288455,0.001975981],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9692882,0.001465809,0.0003240979,0.005853049,0.000400457,0.001117873,0.0003376656,0.005269398,0.0159435],"genre_scores_gemma":[0.9965027,0.001219549,0.00131081,0.0002675752,0.0001909671,0.0002482999,0.00003848843,0.0001760317,0.00004560006],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9823275,"threshold_uncertainty_score":0.9996755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04843245285637655,"score_gpt":0.2679447319991405,"score_spread":0.219512279142764,"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."}}