{"id":"W2346285437","doi":"10.1016/j.patrec.2016.04.009","title":"A spectral graph wavelet approach for nonrigid 3D shape retrieval","year":2016,"lang":"en","type":"article","venue":"Pattern Recognition Letters","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":47,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Pattern recognition (psychology); Heat kernel signature; Artificial intelligence; Geodesic; Wavelet; Embedding; Graph; Mathematics; Computer science; Kernel (algebra); Feature (linguistics); Active shape model; Theoretical computer science","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":[0.0003322173,0.0004894321,0.0005755778,0.001251149,0.0002804234,0.0008460444,0.00102161,0.0007924851,0.002996993],"category_scores_gemma":[0.001031648,0.0003066331,0.0007098445,0.00158706,0.0004837347,0.001351994,0.001047511,0.0008570273,0.001773074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002687892,"about_ca_system_score_gemma":0.0004366617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001881525,"about_ca_topic_score_gemma":0.002574644,"domain_scores_codex":[0.9997403,0.00004828497,0.0000136237,0.00003450413,0.0001387432,0.00002463031],"domain_scores_gemma":[0.9996957,0.00008263592,0.00002164105,0.00008466757,0.00009212964,0.00002327026],"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":[0.0001622015,0.0001627162,0.0003726863,0.0002009949,0.00006590378,0.0001671413,0.0001114178,0.1191568,0.1117177,0.07176716,0.005822182,0.6902931],"study_design_scores_gemma":[0.00000597041,0.00002453215,0.0001660387,0.000005034546,0.000009570305,0.00007025218,0.00001968559,0.9803153,0.004645731,0.01272334,0.002001286,0.00001328421],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004086771,0.0001323766,0.9947513,0.00006141495,0.00002827725,0.00001471762,0.00004712703,0.0001883733,0.0006897267],"genre_scores_gemma":[0.1176868,0.0008010454,0.8758239,0.0001565171,0.00009737191,0.0000682661,0.0004966112,0.0002896826,0.004579823],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002996993,"threshold_uncertainty_score":0.01002592,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02381867800675932,"score_gpt":0.2115676824709552,"score_spread":0.1877490044641959,"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."}}