{"id":"W4280505066","doi":"10.1007/978-981-19-0507-0_27","title":"Structural Defects Classification and Detection Using Convolutional Neural Network (CNN): A Review","year":2022,"lang":"en","type":"review","venue":"Lecture notes in civil engineering","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lakehead University","funders":"","keywords":"Convolutional neural network; Computer science; Classifier (UML); Artificial intelligence; Initialization; Machine learning; Deep learning; Artificial neural network; Data mining; Pattern recognition (psychology)","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002340839,0.0006340636,0.001133849,0.0002769246,0.0001278495,0.00004928194,0.0002009822,0.0003172542,0.00006034099],"category_scores_gemma":[0.0001956961,0.000621441,0.000230685,0.0008010478,0.00002526063,0.000138531,0.00009340866,0.001432579,0.000001289547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007726765,"about_ca_system_score_gemma":0.00004995485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001177335,"about_ca_topic_score_gemma":0.00005802375,"domain_scores_codex":[0.9980281,0.00006895561,0.0006213725,0.0004361898,0.0002398547,0.000605515],"domain_scores_gemma":[0.9991438,0.0003190212,0.0001363246,0.0002975327,0.00002171365,0.00008165005],"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":[0.000001236809,0.000001059619,0.00001919268,0.0230104,0.00005359585,0.00001288582,0.00002062969,0.5835543,0.00002882653,0.00001733405,0.000007204196,0.3932733],"study_design_scores_gemma":[0.0001985454,0.00002871693,0.0001652492,0.02605311,0.0005186193,0.0005528948,0.000001882738,0.6295331,0.000008158045,0.0001092159,0.3416216,0.001208922],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0002767734,0.9781574,0.01805906,0.000002657992,0.002538255,0.0006454539,0.0000118899,0.0002803659,0.00002816534],"genre_scores_gemma":[0.02931101,0.9683667,0.0008985819,0.00002495816,0.001019421,0.0001548798,0.0000707842,0.0001529629,6.342678e-7],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.3920644,"threshold_uncertainty_score":0.9996237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03080464034121112,"score_gpt":0.2636399837064709,"score_spread":0.2328353433652598,"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."}}