{"id":"W4200370932","doi":"10.1145/3478513.3480511","title":"AdaptiBrush","year":2021,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Human Motion and Animation","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Ribbon; Controller (irrigation); Computer science; Path (computing); Orientation (vector space); Trajectory; Point (geometry); Computer vision; Artificial intelligence; Geometry; 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":[0.0003550933,0.001030252,0.0007422207,0.0005759268,0.0004633055,0.001312333,0.003092943,0.0009339209,0.06462961],"category_scores_gemma":[0.002179452,0.000660614,0.0007932074,0.0004166621,0.0004744118,0.001665054,0.003015933,0.001154348,0.02018249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004645326,"about_ca_system_score_gemma":0.0005552516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001822168,"about_ca_topic_score_gemma":0.002900564,"domain_scores_codex":[0.9996183,0.00002153274,0.00002432753,0.0001035306,0.0001769836,0.00005529483],"domain_scores_gemma":[0.9994728,0.0001071315,0.00003211024,0.0001938064,0.0001241266,0.00006995646],"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":[0.001860305,0.0003890104,0.003526374,0.00109334,0.0001214501,0.0006224121,0.0006910214,0.01758966,0.1057445,0.01297222,0.164207,0.6911827],"study_design_scores_gemma":[0.0003299649,0.0007853369,0.005947052,0.0002006171,0.0001191685,0.001667093,0.0002617796,0.2295801,0.1088831,0.01582271,0.6360124,0.00039068],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04333156,0.001387508,0.5277713,0.0003583638,0.0006861403,0.0008873863,0.005125857,0.3195826,0.1008693],"genre_scores_gemma":[0.434735,0.001465424,0.3403393,0.001558301,0.0001743611,0.002146363,0.0144756,0.03358186,0.1715238],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06462961,"threshold_uncertainty_score":0.2162076,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02216906783132329,"score_gpt":0.2231385878089425,"score_spread":0.2009695199776192,"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."}}