{"id":"W2125258143","doi":"10.1109/ijcnn.2006.246873","title":"Self-Organizing Feature Map (SOFM) based Deformable CAD Models","year":2006,"lang":"en","type":"article","venue":"The 2006 IEEE International Joint Conference on Neural Network Proceedings","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Polygon mesh; Computer science; Feature (linguistics); Hexahedron; Point (geometry); Artificial intelligence; Surface (topology); Computer vision; Object (grammar); Topology (electrical circuits); Solid modeling; Algorithm; Geometry; Computer graphics (images); Finite element method; Mathematics; Engineering","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":[0.0002309912,0.0003194131,0.0003227601,0.000612559,0.0002483707,0.0006016713,0.0007930982,0.0006766043,0.001899424],"category_scores_gemma":[0.0009330173,0.000243629,0.0005885765,0.0005382429,0.0003646291,0.0006723333,0.00057153,0.0003839966,0.0003574581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003960544,"about_ca_system_score_gemma":0.0003611179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002934586,"about_ca_topic_score_gemma":0.003493976,"domain_scores_codex":[0.9998174,0.00002657162,0.000007036843,0.00003240052,0.0001010195,0.0000154952],"domain_scores_gemma":[0.9997901,0.00009325521,0.00002304995,0.00003939117,0.0000436486,0.00001059902],"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":[0.00004807985,0.0000345385,0.0007131665,0.00005819288,0.0000278155,0.0001602839,0.0001517994,0.8474392,0.009676212,0.01611624,0.001529598,0.1240449],"study_design_scores_gemma":[0.000001972456,0.000007863263,0.0001232166,0.000002323474,0.00000171715,0.00003015438,0.000004830884,0.9961445,0.0008143283,0.001953335,0.0009112642,0.000004471427],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02035225,0.0000827429,0.976204,0.00008313015,0.00002195276,0.00003076928,0.00009530228,0.0007014699,0.002428259],"genre_scores_gemma":[0.6283318,0.000218995,0.3670255,0.00008812045,0.00002689971,0.0001565355,0.0003027279,0.0001566212,0.003692736],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002934586,"threshold_uncertainty_score":0.006354213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02459641998879341,"score_gpt":0.2130526220363966,"score_spread":0.1884562020476032,"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."}}