{"id":"W3173248865","doi":"10.11159/icsect21.lx.106","title":"Use of Artificial Neural Networks for Prediction of Properties of Self-Sensing Concrete","year":2021,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Civil, Structural, and Environmental Engineering","topic":"Sensor Technology and Measurement Systems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Silesian University of Technology","keywords":"Artificial neural network; Computer science; Artificial intelligence; Machine learning","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006638185,0.001113485,0.000428763,0.0007352438,0.0001996939,0.0005587765,0.0004738539,0.0008439505,0.0005227873],"category_scores_gemma":[0.001625512,0.0003081629,0.0005690053,0.0004836127,0.0001696922,0.0005848726,0.0002572474,0.0006474094,0.000142512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005677303,"about_ca_system_score_gemma":0.0003325954,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00801221,"about_ca_topic_score_gemma":0.006351049,"domain_scores_codex":[0.9998071,0.00006113965,0.00002040558,0.00005073679,0.00003487225,0.00002578145],"domain_scores_gemma":[0.9994105,0.0003888048,0.00005045548,0.00002808378,0.0001043207,0.00001773578],"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":[0.0001928375,0.0002477509,0.008709564,0.00006078274,0.0001264554,0.00007578433,0.00002740168,0.9239826,0.004010222,0.0002475173,0.000444413,0.0618747],"study_design_scores_gemma":[0.000001507481,0.00001629836,0.0007227614,0.000002844846,0.000004887061,0.000002627872,0.000003665899,0.9984455,0.000692265,0.00006929496,0.00003594783,0.000002462304],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8200177,0.001566112,0.1734937,0.0003807089,0.0001308117,0.00007652777,0.0006196409,0.001006724,0.002708141],"genre_scores_gemma":[0.9787006,0.0002557012,0.0195457,0.00002873666,0.00001349083,0.00005458312,0.0004799135,0.00001198527,0.0009091667],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00801221,"threshold_uncertainty_score":0.01593113,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01914695328044846,"score_gpt":0.1806166202627637,"score_spread":0.1614696669823152,"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."}}