{"id":"W4319786764","doi":"10.3390/buildings13020464","title":"Near Real-Time 3D Reconstruction and Quality 3D Point Cloud for Time-Critical Construction Monitoring","year":2023,"lang":"en","type":"article","venue":"Buildings","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"State Key Laboratory of Hydroscience and Engineering; China Scholarship Council; Tsinghua University","keywords":"Point cloud; Robustness (evolution); Benchmark (surveying); Computer science; Cloud computing; Real-time computing; Odometry; 3D reconstruction; Artificial intelligence; Computer vision; Data mining; Simulation; Robot; Mobile robot","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":[0.0007866448,0.0001186481,0.0001797834,0.00003867315,0.000413737,0.0001445387,0.00006625848,0.00009530489,0.0003660424],"category_scores_gemma":[0.0002720915,0.0001054905,0.00004697856,0.0001872377,0.0001872452,0.0002743038,0.00001106107,0.00009715885,0.0002921032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007628837,"about_ca_system_score_gemma":0.00001883912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009112393,"about_ca_topic_score_gemma":0.00002173035,"domain_scores_codex":[0.9989457,0.00008899695,0.0002281942,0.0002940994,0.000146999,0.0002959946],"domain_scores_gemma":[0.9992709,0.0003976778,0.00005329373,0.00009886638,0.00006038172,0.0001188644],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001973446,0.00001030321,0.5510898,0.000168549,0.00003729127,0.000006500909,0.0006948914,0.000192502,0.01461741,0.0003509694,0.001657268,0.4309772],"study_design_scores_gemma":[0.001407208,0.0005283473,0.9281282,0.0003344897,0.00008836149,0.0003651147,0.001998582,0.04741043,0.00340329,0.004815968,0.01030736,0.001212656],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965724,0.00006162979,0.00006128027,0.0002133143,0.0008695102,0.0001370484,0.00008971162,0.0002554102,0.001739668],"genre_scores_gemma":[0.9515261,0.0001539104,0.04621981,0.00003060451,0.0007673409,0.000005567218,0.0001178731,0.00001116625,0.001167639],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4297645,"threshold_uncertainty_score":0.4301777,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03156474067085496,"score_gpt":0.2751309627858628,"score_spread":0.2435662221150078,"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."}}