{"id":"W2567927519","doi":"10.1016/j.jvcir.2017.01.001","title":"Spectral shape classification: A deep learning approach","year":2017,"lang":"en","type":"article","venue":"Journal of Visual Communication and Image Representation","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Artificial intelligence; Pattern recognition (psychology); Deep learning; Computer science; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003877922,0.00007568706,0.0001540251,0.0001040245,0.000350032,0.0003124011,0.0002605092,0.00004014287,0.0000224732],"category_scores_gemma":[0.0001560297,0.00007140815,0.00007439098,0.00005885784,0.00007202233,0.0006595647,0.00004168295,0.0002864358,0.000004322886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002580231,"about_ca_system_score_gemma":0.000007848323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007990086,"about_ca_topic_score_gemma":0.000001683101,"domain_scores_codex":[0.9992817,0.00009043929,0.0003170657,0.00007126837,0.0001592566,0.00008024539],"domain_scores_gemma":[0.9991274,0.00004583519,0.0002988741,0.0003005471,0.0001702561,0.00005701626],"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":[0.0001500248,0.0005317668,0.03190311,0.0002549233,0.0007567043,0.00001351321,0.008133369,0.08583483,0.1406543,0.001233835,0.001189677,0.729344],"study_design_scores_gemma":[0.000307033,0.00003157938,0.02706661,0.00002454031,0.00004649964,0.00002924491,0.001060053,0.9704196,0.0006419087,0.0001618602,0.0001325182,0.00007858512],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7759793,0.00185524,0.2037541,0.0006326522,0.00007860034,0.00008128567,5.304944e-7,0.00006595092,0.0175524],"genre_scores_gemma":[0.986241,0.002861198,0.01070702,0.000008459073,0.00008765814,0.000002132681,0.00001004946,0.00001219225,0.00007032799],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8845847,"threshold_uncertainty_score":0.3012491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04888501279126743,"score_gpt":0.34937353450696,"score_spread":0.3004885217156925,"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."}}