{"id":"W3169626734","doi":"10.1142/s0219622021500425","title":"A Grey Wolf Optimization-Based Method for Segmentation and Evaluation of Scaling in Reinforced Concrete Bridges","year":2021,"lang":"en","type":"article","venue":"International Journal of Information Technology & Decision Making","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Scaling; Segmentation; Artificial neural network; Artificial intelligence; Pattern recognition (psychology); Data mining; Algorithm; Mathematics","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":[0.001025549,0.00009200157,0.0001840172,0.001002916,0.00002869447,0.00005841763,0.0001573395,0.0001230086,0.00001687367],"category_scores_gemma":[0.00119285,0.00009205331,0.00005494606,0.0002633828,0.00002281568,0.0007770201,0.00002848936,0.0001447087,3.426526e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002090592,"about_ca_system_score_gemma":0.0001110305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001151264,"about_ca_topic_score_gemma":0.000001315756,"domain_scores_codex":[0.9984816,0.00002313147,0.0008594718,0.0000610678,0.0004751237,0.00009959119],"domain_scores_gemma":[0.996856,0.0002413476,0.0004495046,0.0000786338,0.00235773,0.00001679375],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005563429,7.775019e-7,0.0004341216,0.00001648702,0.0000321122,0.000001757057,0.0001779711,0.8110355,0.002257331,0.0006693878,0.00001872838,0.1853002],"study_design_scores_gemma":[0.001646899,0.00002537959,0.0004671849,0.0004828453,0.00002655092,0.00007253617,0.0008483256,0.9441915,0.05027533,0.001803262,0.00008399654,0.00007623561],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1841413,0.0001192207,0.8147719,0.0001238376,0.0006185776,0.0001236915,0.000007094999,0.00002066924,0.00007367722],"genre_scores_gemma":[0.6416041,0.00003488875,0.3582569,0.00004526035,0.00003348232,0.000008356763,0.00001105991,0.000005395347,4.986824e-7],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4574628,"threshold_uncertainty_score":0.3753825,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01012577909231719,"score_gpt":0.3176952331077206,"score_spread":0.3075694540154034,"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."}}