{"id":"W2187352959","doi":"","title":"AUTOMATIC 3D BUILDING MODEL GENERATION USING A HYBRID APPROACH","year":2012,"lang":"en","type":"article","venue":"","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of Calgary","funders":"","keywords":"Computer science; Lidar; Matching (statistics); Data mining; Focus (optics); Model building; Data collection; Artificial intelligence; Computer vision; Remote sensing; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004370079,0.0009125894,0.0009325587,0.001941889,0.0004097971,0.001280256,0.001806766,0.001049453,0.002861874],"category_scores_gemma":[0.0008841715,0.0009367982,0.001729826,0.001392739,0.0004785148,0.001151958,0.001722947,0.0007026581,0.001332765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004002726,"about_ca_system_score_gemma":0.0007433121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003916853,"about_ca_topic_score_gemma":0.005377302,"domain_scores_codex":[0.9993265,0.00006915512,0.00003500012,0.0001779473,0.0003238546,0.00006754793],"domain_scores_gemma":[0.9995266,0.0001433235,0.00004045112,0.0001300148,0.0001341175,0.00002547168],"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":[0.0001546328,0.0001267745,0.001077854,0.0002346856,0.0001296157,0.0002903293,0.0002515092,0.4255608,0.0574314,0.006345855,0.002604874,0.5057917],"study_design_scores_gemma":[0.000006486082,0.00002331713,0.0001866548,0.00000627599,0.00001076319,0.00008836358,0.00002514359,0.9914334,0.005121574,0.001533274,0.001550297,0.00001457837],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004835035,0.00006488618,0.9928957,0.00002411041,0.000009857133,0.0000386372,0.00005537269,0.001465393,0.0006109831],"genre_scores_gemma":[0.1419615,0.0001458047,0.8550732,0.00006456571,0.00001703599,0.0001405201,0.0007774647,0.0003393586,0.00148055],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003916853,"threshold_uncertainty_score":0.009573996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04488145221470147,"score_gpt":0.2649439667155955,"score_spread":0.220062514500894,"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."}}