{"id":"W4386813605","doi":"10.1016/j.matpr.2023.09.126","title":"Machine learning-based apparent activation energy estimation for cementitious composites incorporating phase change materials","year":2023,"lang":"en","type":"article","venue":"Materials Today Proceedings","topic":"Phase Change Materials Research","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Materials science; Cement; Cementitious; Composite material; Mortar; Curing (chemistry); Compressive strength; Phase change; Latent heat; Thermodynamics","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":[0.000390126,0.0004028132,0.0003635984,0.0005113407,0.0001730379,0.0003811,0.0004826613,0.0004888342,0.0007679298],"category_scores_gemma":[0.001030248,0.0002177208,0.0003231483,0.0003243391,0.0001974742,0.0005685347,0.0002103746,0.0004858866,0.0002526332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003031739,"about_ca_system_score_gemma":0.000304962,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002177953,"about_ca_topic_score_gemma":0.00319113,"domain_scores_codex":[0.9999191,0.00001976279,0.000004952287,0.00002095276,0.00002497588,0.00001012594],"domain_scores_gemma":[0.9996557,0.0002132985,0.00003756166,0.00001979625,0.00006530304,0.000008298583],"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":[0.0002520191,0.0001438467,0.001854347,0.00008415026,0.00003370168,0.00004109201,0.00002525449,0.8231766,0.03911045,0.001497645,0.0004645116,0.1333163],"study_design_scores_gemma":[8.088088e-7,0.000005175194,0.0001406453,6.874176e-7,0.00000130886,0.000002225768,9.846183e-7,0.9976254,0.00201365,0.0001652307,0.00004234981,0.000001464156],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2837013,0.0004802797,0.7123445,0.0001450806,0.0000370154,0.00003005835,0.0001060809,0.001321304,0.00183443],"genre_scores_gemma":[0.9246911,0.0001067448,0.07367704,0.0000204818,0.00001040385,0.00002478331,0.0001430995,0.0000580741,0.001268348],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002177953,"threshold_uncertainty_score":0.004330575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05477973268110931,"score_gpt":0.2998703247115072,"score_spread":0.2450905920303978,"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."}}