{"id":"W2138544664","doi":"10.1061/(asce)cp.1943-5487.0000072","title":"Analytical Approach to Augmenting Site Photos with 3D Graphics of Underground Infrastructure in Construction Engineering Applications","year":2010,"lang":"en","type":"article","venue":"Journal of Computing in Civil Engineering","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Natural Resources","funders":"","keywords":"Position (finance); Computer science; Orientation (vector space); Process (computing); Graphics; Object (grammar); Focus (optics); Perspective (graphical); Computer graphics (images); Computer graphics; Computer vision; Virtual image; Artificial intelligence","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":[0.0004212566,0.0005428463,0.0003324315,0.001268247,0.0003850789,0.001301399,0.001196228,0.0004589868,0.004066567],"category_scores_gemma":[0.002198074,0.000614614,0.0005691834,0.0007764798,0.0007225089,0.001208706,0.001098632,0.0005120463,0.0008461863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006916912,"about_ca_system_score_gemma":0.0007199723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00215391,"about_ca_topic_score_gemma":0.003752746,"domain_scores_codex":[0.9995129,0.00011174,0.00001290838,0.00005028306,0.0002880202,0.00002426577],"domain_scores_gemma":[0.9994306,0.000247716,0.00004791717,0.0001017509,0.0001524297,0.00001959997],"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":[0.00009368554,0.0001118107,0.001405048,0.0005243515,0.00005491879,0.000626197,0.00104925,0.3613096,0.07359397,0.1715118,0.004360219,0.3853591],"study_design_scores_gemma":[0.00001057249,0.0000525131,0.0008143334,0.0000562534,0.00002485506,0.0003923004,0.0003200474,0.9332058,0.0163875,0.02859063,0.0200902,0.00005494651],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003221154,0.00005159687,0.9936213,0.00007462146,0.00001431394,0.00002589802,0.00001910223,0.000291328,0.002680654],"genre_scores_gemma":[0.1781182,0.0004731409,0.8184634,0.00004608868,0.00003423743,0.00009430503,0.0000654026,0.0001317271,0.002573565],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004066567,"threshold_uncertainty_score":0.01360399,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005725873333633238,"score_gpt":0.1888548472757828,"score_spread":0.1831289739421495,"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."}}