{"id":"W4405495733","doi":"10.1007/978-3-031-61503-0_10","title":"Integrated Framework Using Computer Vision and Ultra-Wide Band Techniques for Progress Reporting in Construction Projects","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in civil engineering","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Construction engineering; Systems engineering; Data science; Engineering; Engineering management","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":[0.000988538,0.0006092844,0.0006055906,0.002635579,0.000396315,0.001628015,0.001202512,0.0007485746,0.003054447],"category_scores_gemma":[0.0007655935,0.0003197177,0.0008342985,0.001972742,0.0002373043,0.001455918,0.001235911,0.0004201621,0.001472838],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005012815,"about_ca_system_score_gemma":0.001386269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009012002,"about_ca_topic_score_gemma":0.01252073,"domain_scores_codex":[0.9992167,0.0001274441,0.0000480101,0.0001784877,0.0003220531,0.0001073376],"domain_scores_gemma":[0.9996474,0.00006868449,0.00003802434,0.00005125945,0.0001612914,0.00003342726],"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":[0.0001346441,0.0002128098,0.004520636,0.0001750297,0.00009319882,0.0001545421,0.0002151533,0.02283329,0.02983969,0.006345666,0.006883095,0.9285923],"study_design_scores_gemma":[0.00003522183,0.0002732941,0.01530026,0.000138043,0.0002410853,0.0005685841,0.000698126,0.8740907,0.04933614,0.008707492,0.05049605,0.0001150215],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01715487,0.0005585271,0.9721283,0.00008428438,0.00005409175,0.0001234512,0.0004314679,0.005175468,0.004289535],"genre_scores_gemma":[0.1876867,0.0006554466,0.8050473,0.00007013896,0.0000400643,0.0002029341,0.001492547,0.0002050057,0.00459992],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009012002,"threshold_uncertainty_score":0.01791912,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01990357731324817,"score_gpt":0.2442559953670098,"score_spread":0.2243524180537616,"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."}}