{"id":"W3186966533","doi":"10.1145/3450626.3459780","title":"Swept volumes via spacetime numerical continuation","year":2021,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Canada Research Chairs; Autodesk","keywords":"Spacetime; Lift (data mining); Representation (politics); Continuation; Computer science; Algorithm; Constructive; Moment (physics); Set (abstract data type); Trajectory; Mathematics; Mathematical optimization; Geometry; Classical mechanics","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":[0.001076886,0.0008345745,0.0007659274,0.001372806,0.0005506468,0.001591766,0.00141822,0.001426187,0.002468792],"category_scores_gemma":[0.00461632,0.0004996982,0.001098607,0.0007165573,0.001762399,0.001460949,0.002979028,0.001660657,0.0008086598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001187865,"about_ca_system_score_gemma":0.001260001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002689355,"about_ca_topic_score_gemma":0.00226792,"domain_scores_codex":[0.9995354,0.0001122565,0.00002284543,0.0000581092,0.0002345361,0.00003682868],"domain_scores_gemma":[0.9990883,0.0004315387,0.0001058044,0.0001730374,0.0001358042,0.00006563324],"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":[0.00008705186,0.00003138192,0.0006862266,0.0001031011,0.00003435793,0.0002436468,0.0002820255,0.7869291,0.008643169,0.1579932,0.001059753,0.04390696],"study_design_scores_gemma":[0.000007662229,0.00001263339,0.00003738803,0.0000150789,0.0000027721,0.0000338663,0.00001429456,0.9696925,0.001108765,0.02725754,0.001808784,0.000008749614],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009969111,0.0001010072,0.9867827,0.00008179637,0.00003077062,0.00002819513,0.00004197727,0.0004550071,0.002509407],"genre_scores_gemma":[0.292517,0.000281941,0.7022119,0.00008491513,0.00004581046,0.0001836654,0.0002115912,0.0005796007,0.003883607],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002689355,"threshold_uncertainty_score":0.008618593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01158228658487209,"score_gpt":0.2180971367990008,"score_spread":0.2065148502141287,"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."}}