{"id":"W2042718509","doi":"10.1145/2558307","title":"Computing smooth surface contours with accurate topology","year":2014,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Advanced Numerical Analysis Techniques","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research","keywords":"Surface (topology); Computer science; Consistency (knowledge bases); Subdivision; Representation (politics); Topology (electrical circuits); Tessellation (computer graphics); Visibility; Algorithm; Mathematics; Computer vision; Artificial intelligence; Computer graphics (images); Geometry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009310889,0.0001732044,0.00022703,0.0001137009,0.0001297583,0.00001709214,0.0002278835,0.00009121602,0.00002502869],"category_scores_gemma":[0.00001423834,0.0001516591,0.00007878368,0.000509614,0.0001094567,0.00009611725,0.000002743684,0.0003515101,0.00001010559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002628753,"about_ca_system_score_gemma":0.000005120374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003620897,"about_ca_topic_score_gemma":0.0001568241,"domain_scores_codex":[0.999225,0.0000381757,0.0001728577,0.0001931271,0.0001245535,0.0002462724],"domain_scores_gemma":[0.9991605,0.0002462932,0.00003313792,0.0004381342,0.00004698173,0.00007491725],"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":[0.00003981591,0.0001052565,0.0006338694,0.0000419002,0.0002448573,0.000005873995,0.0001755972,0.9171088,0.002401863,0.002956488,0.0001510387,0.07613459],"study_design_scores_gemma":[0.002392359,0.001657376,0.005354734,0.0002215407,0.0005751604,0.0000586149,0.0005388268,0.822581,0.08373092,0.0400942,0.0401978,0.002597492],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08218086,0.00003015134,0.9160138,0.0003483675,0.00006842695,0.00007833451,0.000004204861,0.0008464516,0.0004294211],"genre_scores_gemma":[0.9602617,0.00009504134,0.03932603,0.0002364968,0.00001709894,0.000005553472,0.00000327857,0.00003521583,0.00001957298],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8780808,"threshold_uncertainty_score":0.618448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01069633877148749,"score_gpt":0.2462554775732553,"score_spread":0.2355591388017678,"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."}}