{"id":"W4391265677","doi":"10.54097/9qknfc57","title":"Artificial Intelligence and Applications in Structural and Material Engineering","year":2023,"lang":"en","type":"article","venue":"Highlights in Science Engineering and Technology","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Artificial intelligence; Engineering","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":[0.000148384,0.0001416541,0.0001514797,0.001105319,0.00006228552,0.00005356488,0.0001347882,0.0001050792,6.70536e-7],"category_scores_gemma":[0.00003837224,0.0001327819,0.000005219736,0.001473479,0.0001760089,0.0001568917,0.0001017614,0.0001776598,0.00000259383],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004275394,"about_ca_system_score_gemma":0.000008319404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008157453,"about_ca_topic_score_gemma":0.000008493193,"domain_scores_codex":[0.9990911,0.000001538544,0.0001880963,0.0002569366,0.00007924321,0.0003831255],"domain_scores_gemma":[0.9997738,0.00003002306,0.00001070985,0.000122793,0.00001361893,0.00004905364],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004004713,0.000004604047,0.004823836,0.000182254,0.000007687934,0.00004742959,0.0007031029,0.1401805,0.2828858,0.5414492,0.00000460742,0.02970698],"study_design_scores_gemma":[0.0001366157,0.00004782476,0.04322903,0.0001726051,0.000006226199,0.00009005442,0.0005536534,0.7131394,0.2287105,0.01133631,0.001898369,0.0006794903],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977041,0.0001153298,0.001072381,0.00009265148,0.0004105471,0.0001203434,0.000003368064,0.0004601968,0.0000211142],"genre_scores_gemma":[0.9980268,0.0002028019,0.001638851,0.000001016302,0.00007168711,0.00004206933,0.000001152395,0.00001380717,0.000001780438],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5729588,"threshold_uncertainty_score":0.5414689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006223425637294456,"score_gpt":0.2154601933061867,"score_spread":0.2092367676688923,"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."}}