{"id":"W4394918829","doi":"10.1021/acs.jpcc.3c06801","title":"Optimizing the Synthesis Parameters of Double Perovskites with Machine Learning Using a Multioutput Regression Model","year":2024,"lang":"en","type":"article","venue":"The Journal of Physical Chemistry C","topic":"Perovskite Materials and Applications","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Agência Nacional do Petróleo, Gás Natural e Biocombustíveis; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Regression; Machine learning; Regression analysis; Artificial intelligence; Computer science; Materials science; Mathematics; Statistics","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":[0.0006799028,0.0007989773,0.0005565775,0.0003349146,0.0002204562,0.0006205885,0.0005960322,0.001076725,0.0008311392],"category_scores_gemma":[0.001495239,0.0004601982,0.000721327,0.0003186141,0.0003131396,0.0006012629,0.0002871595,0.0009754359,0.0001722911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007891621,"about_ca_system_score_gemma":0.0009065039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006613316,"about_ca_topic_score_gemma":0.006156396,"domain_scores_codex":[0.9998078,0.00004746914,0.00001216723,0.00006069589,0.00004389914,0.00002803985],"domain_scores_gemma":[0.9993538,0.0004627562,0.00005714562,0.00002943291,0.00008462215,0.00001221543],"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":[0.00002348302,0.00002712484,0.0004144194,0.00003422975,0.00001105987,0.00001633769,0.00001000718,0.990382,0.003210853,0.0003347321,0.00007052336,0.005465263],"study_design_scores_gemma":[0.000001755962,0.000006168056,0.0000416907,0.000001196385,0.000001872186,0.000001441498,0.000001027107,0.9986404,0.001184744,0.00008299294,0.00003505339,0.000001606615],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3440413,0.0005406042,0.6500121,0.0003969242,0.00004780986,0.000100442,0.0003088953,0.001078425,0.003473491],"genre_scores_gemma":[0.9142615,0.0001550614,0.08368736,0.00005474987,0.00000968983,0.0001540453,0.0001755518,0.00006074881,0.001441222],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006613316,"threshold_uncertainty_score":0.01314962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01964911517275598,"score_gpt":0.2443017016247778,"score_spread":0.2246525864520219,"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."}}