{"id":"W4396772995","doi":"10.2175/193864718825159365","title":"Accuracy and Project Cost Comparison Between Photogrammetry and LiDAR-based Methods in Sewer Manhole Inspection Data Capture and Condition Assessment","year":2024,"lang":"en","type":"article","venue":"Proceedings of the Water Environment Federation","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Photogrammetry; Lidar; Automatic identification and data capture; Computer science; Environmental science; Remote sensing; Geology; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003262873,0.0001227075,0.0001331164,0.00008126414,0.00009284358,0.0002486663,0.00006061698,0.00006972652,0.000002642453],"category_scores_gemma":[0.000008436896,0.00007701795,0.00001076991,0.00004544459,0.00004490394,0.000443157,0.00009870483,0.0001955769,2.183487e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008465141,"about_ca_system_score_gemma":0.000004138326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004283965,"about_ca_topic_score_gemma":0.000005944964,"domain_scores_codex":[0.9993513,0.00001116823,0.0001887652,0.0002164894,0.000107516,0.0001248079],"domain_scores_gemma":[0.9998441,0.00002672066,0.00003228209,0.00007031255,0.000007317799,0.00001920417],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002420355,0.00003495034,0.2147269,0.001294468,0.00009891637,8.811054e-7,0.004272863,0.001065886,0.7059147,0.0001149229,0.0004839386,0.07196737],"study_design_scores_gemma":[0.0005992731,0.00006741378,0.141816,0.0003089198,0.0001143579,0.000008673165,0.001389412,0.2475834,0.6018796,0.000403693,0.005541394,0.0002878426],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9820831,0.0002047037,0.01659474,0.0001957094,0.0001486722,0.0005605432,0.00001565451,0.00006285354,0.0001340587],"genre_scores_gemma":[0.9929237,0.00009574962,0.006784133,0.00001048998,0.00006979853,0.00003542093,0.00005344804,0.00001628819,0.0000109149],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2465176,"threshold_uncertainty_score":0.3140701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02396635461531695,"score_gpt":0.3231925116434066,"score_spread":0.2992261570280897,"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."}}