{"id":"W1985851765","doi":"10.1007/s00530-013-0318-0","title":"Spatially aggregating spectral descriptors for nonrigid 3D shape retrieval: a comparative survey","year":2013,"lang":"en","type":"article","venue":"Multimedia Systems","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":73,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Heat kernel signature; Pattern recognition (psychology); Artificial intelligence; Geodesic; Computer science; Kernel (algebra); Hyperspectral imaging; Invariant (physics); Codebook; Mathematics; Segmentation; Active shape model; Geometry","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":[0.001975955,0.0007841352,0.001889124,0.003997718,0.000380513,0.001646356,0.00147158,0.0007462099,0.002245238],"category_scores_gemma":[0.003257852,0.0004333121,0.0009608229,0.007445338,0.0007368788,0.002638544,0.001056377,0.0004405097,0.001257744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004211893,"about_ca_system_score_gemma":0.0006155807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002366748,"about_ca_topic_score_gemma":0.002605674,"domain_scores_codex":[0.9984976,0.0002260867,0.0001316795,0.000235725,0.0008347745,0.00007423891],"domain_scores_gemma":[0.997885,0.0007794689,0.0001751232,0.0004137313,0.0007034405,0.00004319888],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009501149,0.0001207183,0.001020262,0.0006684584,0.00008683511,0.00001944135,0.00006775158,0.00615087,0.01120662,0.002940582,0.001583493,0.9760399],"study_design_scores_gemma":[0.0001307807,0.002783932,0.03044285,0.0009365344,0.001148106,0.004163183,0.002180614,0.6147329,0.1324565,0.03978323,0.1707851,0.0004562463],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.05774892,0.1723595,0.7562174,0.0004560793,0.000281035,0.0002363825,0.0003908257,0.0009576404,0.01135233],"genre_scores_gemma":[0.3461325,0.1538172,0.488896,0.0003711368,0.000722324,0.0001806198,0.00150706,0.0003263475,0.008046817],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.003997718,"threshold_uncertainty_score":0.01044995,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07224517236464792,"score_gpt":0.2944845056575718,"score_spread":0.2222393332929239,"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."}}