{"id":"W4395113654","doi":"10.1063/5.0187208","title":"Exploring the optimal design space of transparent perovskite solar cells for four-terminal tandem applications through Pareto front optimization","year":2024,"lang":"en","type":"article","venue":"APL Machine Learning","topic":"Perovskite Materials and Applications","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Solar Energy Research Institute of Singapore, National University of Singapore; Energy Market Authority of Singapore; Economic Development Board - Singapore; National Research Foundation Singapore","keywords":"Tandem; Terminal (telecommunication); Front (military); Space (punctuation); Multi-objective optimization; Computer science; Mathematical optimization; Optimal design; Materials science; Mechanical engineering; Aerospace engineering; Mathematics; Engineering; Telecommunications; Operating system","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000263422,0.000194584,0.0002061529,0.00005523769,0.0002321575,0.0001162117,0.0001931798,0.00004704239,0.00005272345],"category_scores_gemma":[0.00001293152,0.0001598709,0.0001020735,0.000165761,0.00003584691,0.000241566,0.00002367441,0.0002134473,0.00001647156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000464138,"about_ca_system_score_gemma":0.00001841671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003001116,"about_ca_topic_score_gemma":0.000005491368,"domain_scores_codex":[0.9990242,0.00004812345,0.0003056201,0.0002410165,0.0001329733,0.000248104],"domain_scores_gemma":[0.9994351,0.0002221254,0.00004688839,0.000208287,0.00004547472,0.00004211111],"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":[0.000007960379,0.00001276216,0.00001607449,0.0001671324,0.00004735277,9.951948e-7,0.001449327,0.96967,0.02296376,0.0005992748,0.0001011982,0.004964145],"study_design_scores_gemma":[0.0001556804,0.0000515292,0.00005554604,0.00008058842,0.00009621437,0.00000693314,0.0001709361,0.9397671,0.02250194,0.0001132177,0.0368046,0.0001957299],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02523818,0.000814262,0.9722866,0.0002432161,0.0001703761,0.0006981648,0.00004247775,0.0003333693,0.0001733201],"genre_scores_gemma":[0.9305085,0.0007655466,0.06690643,0.00001414027,0.0002230637,0.001358284,0.00007308483,0.00007547279,0.00007551281],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9053802,"threshold_uncertainty_score":0.6519346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07283197211021232,"score_gpt":0.258979697979707,"score_spread":0.1861477258694947,"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."}}