{"id":"W4392755020","doi":"10.1016/j.jeurceramsoc.2024.03.035","title":"Digital precision in engineered ceramics: Tailoring toughness and flexibility through interlocking strategies","year":2024,"lang":"en","type":"article","venue":"Journal of the European Ceramic Society","topic":"Building materials and conservation","field":"Earth and Planetary Sciences","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Research Council Canada","funders":"National Research Council Canada","keywords":"Interlocking; Tile; Materials science; Ceramic; Toughness; Composite material; Finite element method; Mechanical engineering; Structural engineering; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0008250646,0.00008859563,0.0001171998,0.00001835937,0.00006459173,0.000644774,0.0001931151,0.00002667167,0.00002292485],"category_scores_gemma":[0.00004110278,0.00005511676,0.0001044179,0.00014014,0.00004855563,0.0008713781,0.00003436281,0.0002307669,0.000003947264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001627971,"about_ca_system_score_gemma":0.00004073668,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004501581,"about_ca_topic_score_gemma":0.00001632663,"domain_scores_codex":[0.9991956,0.0001106644,0.0003111274,0.0001179951,0.0001482183,0.0001164045],"domain_scores_gemma":[0.9996426,0.0001237401,0.00009148996,0.00009118071,0.00002859261,0.00002243485],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001494404,0.0000574251,0.2376837,0.0004923312,0.0002272117,0.00009669854,0.02264068,0.0777056,0.005956012,0.0006351941,0.001818367,0.6525373],"study_design_scores_gemma":[0.0005723658,0.0001472159,0.9110822,0.001299158,0.0000424313,0.0002462349,0.006372757,0.0607053,0.0004747444,0.01106836,0.007666109,0.0003230909],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941291,0.0009823079,0.0006981193,0.0003182023,0.001149222,0.00005266849,0.00001077248,0.00001852418,0.002641149],"genre_scores_gemma":[0.9990757,0.0001935479,0.0003485733,0.00004929349,0.0002663934,4.672587e-8,0.000001995876,0.000005445156,0.00005907995],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6733985,"threshold_uncertainty_score":0.621757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02154681766760105,"score_gpt":0.2318720758256201,"score_spread":0.2103252581580191,"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."}}