{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004939803,0.00009339587,0.00009868946,0.0001896406,0.00005479515,0.00001623266,0.0001465938,0.00006560569,0.0001826487],"category_scores_gemma":[0.000002662245,0.00009299973,0.000136033,0.0003601337,0.00001220321,0.00005452053,7.948602e-7,0.0002094035,0.0002876886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000119375,"about_ca_system_score_gemma":0.000003833287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007849304,"about_ca_topic_score_gemma":0.00002433058,"domain_scores_codex":[0.9995304,0.000007135713,0.0001007482,0.0001124192,0.000111971,0.0001373502],"domain_scores_gemma":[0.9994885,0.00003746312,0.000006466792,0.0004039057,0.00001855735,0.0000451435],"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":[0.000005183131,0.00006979999,0.0003288962,0.00004762528,0.0002411856,0.000002357931,0.0002360015,0.9679988,0.001130916,0.0005523653,0.0003420606,0.0290448],"study_design_scores_gemma":[0.0006948042,0.0001120692,0.0008366372,0.0000671486,0.0001875296,0.000007487477,0.0001893574,0.9763405,0.004046067,0.008345327,0.008483428,0.000689585],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2985144,0.0001067689,0.6970834,0.000328674,0.0004210268,0.0000781097,0.00001966671,0.0006349548,0.00281304],"genre_scores_gemma":[0.998428,0.0002251031,0.0007805249,0.0001444107,0.00001424858,0.000006710205,0.000004122216,0.00002296026,0.000373854],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6999137,"threshold_uncertainty_score":0.3792419,"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."}}