{"id":"W4411022830","doi":"10.1016/j.eng.2025.03.036","title":"Progress of Machine Learning in Molecular Crystal Design and Crystallization Development","year":2025,"lang":"en","type":"article","venue":"Engineering","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"China Scholarship Council; Key Technology Research and Development Program of Shandong; National Natural Science Foundation of China; Innovative Research Group Project of the National Natural Science Foundation of China","keywords":"Crystallization; Development (topology); Crystal (programming language); Materials science; Computer science; Nanotechnology; Engineering; Chemical engineering; Mathematics; Programming language","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":[0.005050513,0.001309691,0.001639644,0.001915897,0.0004669646,0.00257712,0.001557295,0.001585588,0.001673639],"category_scores_gemma":[0.007450887,0.0006935393,0.001270478,0.002561106,0.001720483,0.003945336,0.001488798,0.004263687,0.0011304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00180406,"about_ca_system_score_gemma":0.001992918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001558517,"about_ca_topic_score_gemma":0.0009264872,"domain_scores_codex":[0.9979091,0.0007046163,0.0001486027,0.0005063394,0.0006329617,0.00009836228],"domain_scores_gemma":[0.9958649,0.002644243,0.0002755056,0.0003333759,0.0007739883,0.0001079491],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001368317,0.0002170564,0.001798029,0.003433835,0.0001963211,0.0001057149,0.0002269992,0.1126709,0.00803908,0.1390678,0.008770649,0.7253367],"study_design_scores_gemma":[0.00006350911,0.000340983,0.001275706,0.0007551917,0.0001213074,0.000229503,0.0001065066,0.6020762,0.03131093,0.1710384,0.1925062,0.0001756214],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.01019811,0.1801063,0.7917956,0.004111852,0.0006531359,0.0001293096,0.000205407,0.0007037551,0.01209673],"genre_scores_gemma":[0.163551,0.2861988,0.5393983,0.001494531,0.002402955,0.000465398,0.000863445,0.0003483587,0.005277248],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.005050513,"threshold_uncertainty_score":0.02670997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005111975102496771,"score_gpt":0.2194083677983597,"score_spread":0.2142963926958629,"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."}}