{"id":"W2552930185","doi":"10.1145/2980179.2980223","title":"Action-driven 3D indoor scene evolution","year":2016,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Naturalness; Computer science; Object (grammar); Action (physics); Artificial intelligence; Computer vision; Graph; Sequence (biology); Human–computer interaction; Theoretical computer science","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":[0.0001302326,0.0001677417,0.0001268487,0.0004746004,0.0004367582,0.00007972783,0.0005600384,0.0001392954,0.0001991322],"category_scores_gemma":[0.00002804024,0.0001313413,0.0001485474,0.0006778821,0.0000773128,0.001033242,0.00001042556,0.0002223878,0.0005209101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001046327,"about_ca_system_score_gemma":0.00006656764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002051958,"about_ca_topic_score_gemma":0.00008752526,"domain_scores_codex":[0.9986848,0.00007920249,0.0002336705,0.0004071751,0.0003223752,0.0002727629],"domain_scores_gemma":[0.9986892,0.0001758941,0.0000883032,0.0007811289,0.0001438359,0.0001215888],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004963501,0.0005873703,0.0005262715,0.00002173426,0.0001312961,0.0000104789,0.0001928412,0.0001021337,0.01304738,0.02086226,0.00106481,0.9634038],"study_design_scores_gemma":[0.01492741,0.003568467,0.09938776,0.001398877,0.000504718,0.0005858844,0.0003628245,0.0384647,0.2242534,0.4753715,0.135689,0.005485525],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01723861,0.00001535163,0.9776267,0.003320452,0.000817173,0.0001532853,0.0000172377,0.000416136,0.0003950761],"genre_scores_gemma":[0.9865913,0.0002117096,0.0120644,0.0005396825,0.00009017086,0.00005221156,0.000002670002,0.00001536959,0.0004324895],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9693527,"threshold_uncertainty_score":0.669542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03580600599429647,"score_gpt":0.2651108026515664,"score_spread":0.22930479665727,"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."}}