{"id":"W2160823495","doi":"10.1111/cgf.12554","title":"Template Assembly for Detailed Urban Reconstruction","year":2015,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Template; Computer science; Point cloud; Texture synthesis; Preprocessor; Consistency (knowledge bases); Artificial intelligence; Set (abstract data type); Computer vision; Computer graphics (images); Structure from motion; Template matching; Matching (statistics); Point (geometry); Image (mathematics); Image texture; Motion (physics); Image processing; Geometry; 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":[0.0006638336,0.0009818807,0.001188067,0.001642864,0.0005203811,0.001572059,0.00156611,0.0008637441,0.004438874],"category_scores_gemma":[0.001950679,0.001106072,0.001536524,0.001323564,0.0008546628,0.001154083,0.001584843,0.001246485,0.001726366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006450222,"about_ca_system_score_gemma":0.001007695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006436239,"about_ca_topic_score_gemma":0.006805575,"domain_scores_codex":[0.9992864,0.0001000507,0.00003400484,0.0001712852,0.0003351446,0.00007326596],"domain_scores_gemma":[0.9991567,0.0001753327,0.00008045947,0.0003946276,0.0001452845,0.00004755147],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001310213,0.00006403173,0.001674449,0.0000997118,0.00009085196,0.0002211214,0.0001582211,0.714449,0.03415509,0.02439807,0.003895219,0.2206631],"study_design_scores_gemma":[0.000005926329,0.00001200639,0.0002000604,0.000004423259,0.000006504747,0.00007091592,0.0000112449,0.9857013,0.006658333,0.004634137,0.002681106,0.0000139911],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003971649,0.00003092333,0.9942063,0.00001896569,0.00001109077,0.0000208211,0.00008221682,0.001029809,0.0006281317],"genre_scores_gemma":[0.1445415,0.0001163337,0.8517213,0.00004756519,0.00002459889,0.00007694132,0.0009026368,0.0008417377,0.001727292],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006436239,"threshold_uncertainty_score":0.01484954,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04345676877828471,"score_gpt":0.2313162280663409,"score_spread":0.1878594592880561,"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."}}