{"id":"W4408605753","doi":"10.1088/2515-7639/adc29d","title":"Artificial intelligence for advanced functional materials: exploring current and future directions","year":2025,"lang":"en","type":"article","venue":"Journal of Physics Materials","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; University of Waterloo; University of Toronto","funders":"Agencia Estatal de Investigación; Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund; Universität Bremen; Generalitat de Catalunya; Eusko Jaurlaritza; National Research Foundation Singapore; European Regional Development Fund; Euskal Herriko Unibertsitatea; European Commission; Centres de Recerca de Catalunya; Deutsche Forschungsgemeinschaft; Ministry of Education - Singapore; University of Toronto; National Research Foundation; UK Research and Innovation; Institut Català de Nanociència i Nanotecnologia; Canadian Institute for Advanced Research","keywords":"Current (fluid); Computer science; Cognitive science; Psychology; Engineering; Electrical 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00316626,0.0005943663,0.0007772252,0.001334342,0.0005769025,0.004403822,0.001133442,0.002859947,0.005345309],"category_scores_gemma":[0.001774779,0.0003225921,0.0004891227,0.001373296,0.002854303,0.008671624,0.001738257,0.002477783,0.0009505516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001154279,"about_ca_system_score_gemma":0.001207809,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007396991,"about_ca_topic_score_gemma":0.001006852,"domain_scores_codex":[0.9994513,0.0002310292,0.00002270667,0.00006345959,0.0001552025,0.00007615906],"domain_scores_gemma":[0.9980289,0.001391099,0.00007305133,0.000106285,0.000247022,0.0001536641],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001292028,0.0002886747,0.001046093,0.002322197,0.00007659176,0.0001927678,0.0004012926,0.01060858,0.001786912,0.7286697,0.02783038,0.2266476],"study_design_scores_gemma":[0.00003085618,0.0001584892,0.0007071148,0.001049874,0.00001767439,0.0001485647,0.0005893686,0.03248386,0.0007208235,0.8008677,0.163177,0.0000486848],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01372727,0.7940194,0.04652876,0.07607378,0.001402507,0.00005159386,0.0001401843,0.0002921539,0.06776437],"genre_scores_gemma":[0.2381381,0.6909843,0.04788655,0.006983084,0.004065516,0.0001700772,0.0002087093,0.00009072998,0.01147285],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005345309,"threshold_uncertainty_score":0.01788187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05770152027477002,"score_gpt":0.3297361517888733,"score_spread":0.2720346315141032,"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."}}