{"id":"W2963601843","doi":"10.1145/3303766","title":"GRAINS","year":2019,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":190,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Computer science; Artificial intelligence; Autoencoder; Encoding (memory); Object (grammar); Computer vision; Decoding methods; Pattern recognition (psychology); Encoder; Semantics (computer science); Segmentation; Generative model; Generative grammar; Artificial neural network; Algorithm","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002364467,0.0007477956,0.0004693327,0.0005864489,0.0003869425,0.001135083,0.001183567,0.0007823458,0.02133089],"category_scores_gemma":[0.0009138023,0.0004915136,0.00115768,0.000465208,0.0005652,0.001088349,0.001381924,0.0008902513,0.005531617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000604763,"about_ca_system_score_gemma":0.0006122123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00313781,"about_ca_topic_score_gemma":0.008776043,"domain_scores_codex":[0.9997186,0.00003263681,0.00001087598,0.0001078266,0.00009734803,0.00003268184],"domain_scores_gemma":[0.9997932,0.00005318862,0.00001462882,0.0000795333,0.00004233761,0.00001705021],"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":[0.0001884314,0.0001016414,0.001959596,0.0003813908,0.000138178,0.0003687753,0.0002089891,0.4204582,0.0311979,0.1324188,0.03398359,0.3785945],"study_design_scores_gemma":[0.0000222332,0.00005288087,0.0004364004,0.00002930272,0.00002711364,0.0002281229,0.00003091771,0.8835872,0.01333953,0.04307359,0.05914288,0.00002989214],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006962551,0.0002135894,0.9669298,0.0001683808,0.0001256274,0.0000807253,0.001113535,0.006044746,0.01836115],"genre_scores_gemma":[0.2677049,0.0004923916,0.693303,0.0005132739,0.00008414148,0.0002805635,0.005807038,0.002813374,0.02900132],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02133089,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0113186223023719,"score_gpt":0.20802341010122,"score_spread":0.1967047877988481,"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."}}