{"id":"W2890848214","doi":"10.1109/icassp.2018.8462291","title":"A Graph-CNN for 3D Point Cloud Classification","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Graph Neural Networks","field":"Computer Science","cited_by":181,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Upsampling; Point cloud; Graph; Pooling; Theoretical computer science; Convolutional neural network; Topological graph theory; Artificial intelligence; Line graph; Voltage graph","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":[0.0001324605,0.00009454395,0.0000865853,0.00006807096,0.0001383226,0.00006206814,0.0005259987,0.00004688062,0.00001283036],"category_scores_gemma":[0.00002557632,0.00007816387,0.00006341984,0.0004130455,0.00008153637,0.0003956301,0.00008827349,0.00005746508,0.00007026896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001418003,"about_ca_system_score_gemma":0.00001355307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000244316,"about_ca_topic_score_gemma":0.00001308833,"domain_scores_codex":[0.9991007,0.00001952606,0.0001591433,0.0003508669,0.0001176285,0.000252119],"domain_scores_gemma":[0.9991072,0.00009273009,0.00006680845,0.0005286792,0.0001345545,0.00006998582],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000157786,0.00003418587,0.0001110263,0.000004602909,0.000008444341,7.307085e-7,0.0001389744,0.00002072133,0.001515641,0.8363355,0.02451079,0.1373036],"study_design_scores_gemma":[0.0005894491,0.0004874213,0.002264607,0.00001362969,0.000006432867,0.00001216251,0.00002507454,0.5666329,0.005463091,0.3441329,0.08001437,0.0003579478],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001088948,0.00002338545,0.9897592,0.001813096,0.000795636,0.0002556259,7.014788e-7,0.00029801,0.005965367],"genre_scores_gemma":[0.4071323,0.000007835086,0.5900615,0.001577865,0.0004270179,0.00004973548,0.00000227149,0.000009413449,0.0007320063],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5666122,"threshold_uncertainty_score":0.318743,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03146337179556759,"score_gpt":0.2832721333078607,"score_spread":0.2518087615122931,"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."}}