{"id":"W2050543800","doi":"10.1145/2766990","title":"Flow aligned surfacing of curve networks","year":2015,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":80,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Curvature; Flow (mathematics); Principal curvature; Surface (topology); Sketch; Line (geometry); Computer science; Mean curvature flow; Computer graphics (images); Graphics; Field (mathematics); Geometry; Artificial intelligence; Computer vision; Topology (electrical circuits); Algorithm; Mathematics; Mean curvature","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009271627,0.001311237,0.001137177,0.002362344,0.0006258353,0.002121333,0.001930827,0.001459346,0.005194626],"category_scores_gemma":[0.004906306,0.0007623142,0.001162384,0.001298109,0.0009976237,0.002941814,0.002128713,0.001526813,0.001203481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007962939,"about_ca_system_score_gemma":0.0007152151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00236928,"about_ca_topic_score_gemma":0.002775059,"domain_scores_codex":[0.9991523,0.000111099,0.00003747485,0.0002903668,0.0003432315,0.00006538598],"domain_scores_gemma":[0.9983347,0.0005377781,0.0002046715,0.0004909455,0.0003156741,0.0001162748],"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":[0.000228233,0.0001112604,0.002265418,0.0002502236,0.00007615364,0.0003637778,0.0008827033,0.3430023,0.08554319,0.03055531,0.002902752,0.5338187],"study_design_scores_gemma":[0.00001084758,0.00007355481,0.0004034088,0.00002002691,0.00000983009,0.0001419819,0.0000955129,0.9659439,0.01489095,0.01378189,0.004601111,0.00002708373],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01291469,0.00006057036,0.9841363,0.00003900458,0.0000157205,0.00005151498,0.00006332161,0.001747018,0.0009717555],"genre_scores_gemma":[0.2518338,0.0002192602,0.7431955,0.00006270268,0.00003822702,0.0001055513,0.0004329748,0.001011376,0.003100622],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005194626,"threshold_uncertainty_score":0.01737779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02864601295580507,"score_gpt":0.2288429869076208,"score_spread":0.2001969739518157,"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."}}