{"id":"W2769969171","doi":"10.1145/3130800.3130823","title":"BigSUR","year":2017,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":77,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Computer science; 3D city models; Parsing; Facade; Polygon mesh; Scale (ratio); Data mining; Artificial intelligence; Computer graphics (images); Visualization; Cartography; Geography","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00008770089,0.00007796819,0.00006015317,0.00003169828,0.00113246,0.00007067102,0.000455219,0.00005699321,0.0004033145],"category_scores_gemma":[0.00002411285,0.00007313043,0.00007242594,0.0000930491,0.0002448193,0.0001130188,0.000008841565,0.0001613582,0.0007859641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001971048,"about_ca_system_score_gemma":0.000004297571,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004284155,"about_ca_topic_score_gemma":0.000401064,"domain_scores_codex":[0.9994158,0.0000128436,0.00008292886,0.0001954996,0.0001573334,0.0001355778],"domain_scores_gemma":[0.9985027,0.00003673407,0.00004634491,0.001339181,0.000005314417,0.00006971559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00003358736,0.000572919,0.009440899,0.000007506793,0.00006650921,0.00001028654,0.0005380269,0.002335103,0.007971624,0.002128947,0.006819632,0.970075],"study_design_scores_gemma":[0.0008716093,0.0001737799,0.536398,0.00003329458,0.0001004619,0.00003979642,0.000100422,0.003408291,0.01524668,0.04766469,0.3952005,0.0007625503],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6027107,0.00001472652,0.2301724,0.01984229,0.0007601972,0.0004498867,0.0000399118,0.0003697039,0.1456402],"genre_scores_gemma":[0.9948144,0.00004782045,0.003583048,0.0003324504,0.00001593737,0.00000368466,0.000001304058,0.00001060675,0.001190737],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9693124,"threshold_uncertainty_score":0.999992,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02485790820213919,"score_gpt":0.2658250356160625,"score_spread":0.2409671274139233,"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."}}