{"id":"W2962780613","doi":"10.1145/3272127.3275008","title":"SCORES","year":2018,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Feature (linguistics); Encoding (memory); Substructure; Code (set theory); Algorithm; Artificial neural network; Range (aeronautics); Artificial intelligence; Autoencoder; Pattern recognition (psychology); Topology (electrical circuits); Set (abstract data type); Mathematics","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":[0.001199896,0.001827944,0.0009281093,0.001603513,0.0007951944,0.003060807,0.002401884,0.001397557,0.08222902],"category_scores_gemma":[0.007701322,0.0005033099,0.001029909,0.001093346,0.000814544,0.004094156,0.003065832,0.001808439,0.02947463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001177915,"about_ca_system_score_gemma":0.001961201,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003639027,"about_ca_topic_score_gemma":0.007714178,"domain_scores_codex":[0.9980472,0.0002837754,0.0001246342,0.0005084754,0.0008122469,0.0002235124],"domain_scores_gemma":[0.9986092,0.0002934317,0.00009137169,0.0003572563,0.0005203167,0.0001283494],"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":[0.000253475,0.0001604882,0.003903548,0.0003624042,0.0001239736,0.0002040026,0.0001161507,0.03572696,0.003055613,0.134581,0.1417881,0.6797244],"study_design_scores_gemma":[0.0001161808,0.0002221396,0.001619655,0.0001655371,0.00009712778,0.0005030861,0.0001171988,0.3297465,0.007450932,0.3288828,0.330984,0.00009488044],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0130401,0.001190646,0.8342996,0.002526944,0.001485408,0.0005511415,0.01051764,0.02451399,0.1118746],"genre_scores_gemma":[0.2942465,0.002037656,0.5085916,0.002691479,0.0008809459,0.001101289,0.0360642,0.00685831,0.1475281],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08222902,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01886306742438699,"score_gpt":0.2345501880263377,"score_spread":0.2156871206019507,"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."}}