{"id":"W4385841629","doi":"10.1016/j.eng.2023.03.021","title":"Intelligent Intercommunicating Multiscale Engineering: The Engineering of the Future","year":2023,"lang":"en","type":"article","venue":"Engineering","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Science and Technology Department of Zhejiang Province; Zhejiang Provincial Government Scholarship","keywords":"Computer science; Artificial intelligence; Systems engineering; Engineering","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":[0.001783272,0.0004759337,0.0008346468,0.0005037143,0.001056639,0.00362156,0.001389236,0.002691366,0.005689747],"category_scores_gemma":[0.003119903,0.0004443291,0.0003751266,0.0004010262,0.004197217,0.007909577,0.002886438,0.002647742,0.00100339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001169684,"about_ca_system_score_gemma":0.001116626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005819474,"about_ca_topic_score_gemma":0.0008500678,"domain_scores_codex":[0.9992883,0.000214727,0.00001783371,0.0001209367,0.0002379785,0.0001202508],"domain_scores_gemma":[0.9982729,0.0006808031,0.0001359191,0.0004229467,0.0002359078,0.0002515684],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002623238,0.00005203417,0.0002983016,0.0001278899,0.00001886117,0.00005090671,0.0001415986,0.01026213,0.003173233,0.954949,0.005149345,0.02575051],"study_design_scores_gemma":[0.00001020628,0.00002519246,0.0002484603,0.00005906179,0.000007679955,0.00004583036,0.0001588831,0.07136432,0.00139836,0.8970806,0.0295784,0.00002291355],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07739434,0.03246161,0.680532,0.05788831,0.002715352,0.00008872238,0.0002145652,0.001073917,0.1476312],"genre_scores_gemma":[0.8457736,0.01123021,0.1252364,0.001898242,0.0009448327,0.0001193375,0.0001174945,0.000212921,0.01446696],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005689747,"threshold_uncertainty_score":0.01903409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008273291122281968,"score_gpt":0.2271458498791707,"score_spread":0.2188725587568887,"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."}}