{"id":"W4382446790","doi":"10.1201/9781003348030-316","title":"Quantitative estimation of TBM disc cutter wear from in-situ parameters by optimization algorithm improved back-propagation neural network: A case study of a metro tunnel in Guangzhou, China","year":2023,"lang":"en","type":"book-chapter","venue":"","topic":"Tunneling and Rock Mechanics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Artificial neural network; Engineering; Algorithm; Computer science; Artificial intelligence","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":[0.0005635263,0.0008909162,0.0006108339,0.001116293,0.0002855225,0.0005433195,0.0008167622,0.0007223127,0.0003637296],"category_scores_gemma":[0.001012057,0.00025045,0.0006283859,0.0009420979,0.0003121842,0.0003370092,0.0003295496,0.0003082884,0.0001127429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008215769,"about_ca_system_score_gemma":0.0005144376,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.052821,"about_ca_topic_score_gemma":0.0553122,"domain_scores_codex":[0.9997472,0.00003060111,0.0000228013,0.00008421396,0.00008169555,0.00003357565],"domain_scores_gemma":[0.9994683,0.0001755795,0.00007762671,0.00005611675,0.0001947417,0.00002765472],"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":[0.0004870717,0.0004188763,0.1412656,0.0004302136,0.0001847732,0.002373,0.0005043661,0.7262523,0.02085795,0.0003659668,0.001614635,0.1052452],"study_design_scores_gemma":[0.00001100871,0.00005716485,0.05068842,0.00001098091,0.00002526689,0.00006052461,0.0001608364,0.9461059,0.002542152,0.0001115296,0.0002105332,0.00001572437],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9872623,0.0001537567,0.0113511,0.0000614521,0.0000136143,0.00002515076,0.0003363231,0.0001571527,0.0006391007],"genre_scores_gemma":[0.9933292,0.00005578962,0.005714172,0.000007605421,0.00000504113,0.00001532565,0.0003718487,0.000008969132,0.000492059],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.052821,"threshold_uncertainty_score":0.1050271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01922394812576252,"score_gpt":0.2357900932138016,"score_spread":0.2165661450880391,"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."}}