{"id":"W4312127315","doi":"10.3390/drones6120407","title":"Texture Analysis to Enhance Drone-Based Multi-Modal Inspection of Structures","year":2022,"lang":"en","type":"article","venue":"Drones","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; Université Laval","keywords":"Segmentation; Modal; Process (computing); Computer science; Visibility; Artificial intelligence; Piping; Pipeline (software); Feature (linguistics); Computer vision; Drone; Visual inspection; Pipeline transport; Pattern recognition (psychology); Engineering; Mechanical engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00005896868,0.0001185095,0.0001909689,0.0002721343,0.0001126765,0.00001032379,0.0001372183,0.00003433554,0.0001130671],"category_scores_gemma":[0.00001058619,0.0001196398,0.00009206428,0.0006568506,0.00001610688,0.00004455179,0.00003710957,0.0001611352,0.000002241232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00010878,"about_ca_system_score_gemma":0.00001207465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000922105,"about_ca_topic_score_gemma":0.00008453653,"domain_scores_codex":[0.9993027,0.00001595843,0.0001633962,0.0001565297,0.0001799252,0.0001814945],"domain_scores_gemma":[0.9996791,0.00001290025,0.00003467913,0.0002024386,0.00003186925,0.00003899692],"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":[0.00001865305,0.00001124056,0.003635079,0.00002515237,0.0001547056,0.000003232203,0.0006267705,0.9338397,0.0576342,0.0001353149,0.0003149503,0.00360099],"study_design_scores_gemma":[0.0006580668,0.0002018058,0.2087594,0.00002016486,0.0004254158,0.000006416618,0.001673458,0.2343974,0.5431594,0.0004091861,0.009493989,0.0007953315],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9126825,0.0001462594,0.08575068,0.00003832171,0.0008035837,0.0001187898,0.00003979166,0.0002135437,0.0002065358],"genre_scores_gemma":[0.9964014,0.000002285057,0.003315342,0.00003614915,0.0001109539,0.00003560984,0.00001890477,0.00001957822,0.00005983357],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6994423,"threshold_uncertainty_score":0.487877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004461149719520462,"score_gpt":0.241826391542421,"score_spread":0.2373652418229006,"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."}}