{"id":"W3160523492","doi":"10.1149/1945-7111/ac00f4","title":"Communication—Design of LiNi <sub>0.2</sub> Mn <sub>0.2</sub> Co <sub>0.2</sub> Fe <sub>0.2</sub> Ti <sub>0.2</sub> O <sub>2</sub> as a High-Entropy Cathode for Lithium-Ion Batteries Guided by Machine Learning","year":2021,"lang":"en","type":"article","venue":"Journal of The Electrochemical Society","topic":"Semiconductor materials and devices","field":"Engineering","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; University of Ottawa","funders":"Office of Energy Research and Development","keywords":"Cathode; Electrochemistry; Materials science; Transition metal; Battery (electricity); Electrode; Lithium (medication); Chemical stability; Chemical engineering; Chemistry; Thermodynamics; Physics; Physical chemistry; 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":[0.0001410379,0.0003577408,0.0002304535,0.0001726683,0.0002693371,0.0005858542,0.0005611805,0.0005113868,0.002124184],"category_scores_gemma":[0.0001858214,0.0001865323,0.000141507,0.0001614195,0.000147437,0.0004438129,0.0003786767,0.0003267817,0.001461252],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005241915,"about_ca_system_score_gemma":0.0003861867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003207594,"about_ca_topic_score_gemma":0.000577174,"domain_scores_codex":[0.9999251,0.000004255774,0.000003696324,0.0000197493,0.00003539364,0.00001178756],"domain_scores_gemma":[0.9999427,0.000002990172,0.00001243354,0.000003617898,0.00002594709,0.00001232897],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001237752,0.00005834294,0.0004109155,0.0002890708,0.00001305499,0.0002272741,0.00007306672,0.003764124,0.9677223,0.004767529,0.002185352,0.02036518],"study_design_scores_gemma":[0.00004110187,0.0003449228,0.0005850421,0.00001853246,0.00001299376,0.0003385037,0.00006149156,0.03747861,0.9270211,0.0009740139,0.03310256,0.00002116244],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8050807,0.004907622,0.1322728,0.002517248,0.0009557669,0.0003824998,0.001012326,0.001082994,0.05178805],"genre_scores_gemma":[0.8998313,0.002334469,0.07501787,0.0002585948,0.00008535702,0.0002242936,0.0007156418,0.0002216152,0.02131073],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002124184,"threshold_uncertainty_score":0.007106125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01328408441288375,"score_gpt":0.2349344940540531,"score_spread":0.2216504096411694,"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."}}