{"id":"W3162539544","doi":"10.1002/aenm.202100332","title":"Defect Engineering for Expediting Li–S Chemistry: Strategies, Mechanisms, and Perspectives","year":2021,"lang":"en","type":"article","venue":"Advanced Energy Materials","topic":"Advanced Battery Materials and Technologies","field":"Engineering","cited_by":260,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Polysulfide; Nanotechnology; Biochemical engineering; Commercialization; Materials science; Chemistry; Engineering; Electrode; Political science","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00006437306,0.0002581502,0.0003286804,0.00003164633,0.00006967733,0.0001330418,0.00009472005,0.0001074723,0.00008716815],"category_scores_gemma":[0.00006857075,0.00027693,0.00004281377,0.0000754876,0.00002672738,0.0003100823,0.00007243633,0.00004548239,9.697295e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004630915,"about_ca_system_score_gemma":0.00001622095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003014026,"about_ca_topic_score_gemma":0.000002033566,"domain_scores_codex":[0.9990029,0.00000874527,0.0002413106,0.000325468,0.00007029283,0.0003513052],"domain_scores_gemma":[0.9995598,0.00006927884,0.00004599671,0.0002230188,0.00005574085,0.00004613557],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000008841226,0.000006175876,1.513863e-7,0.0001655271,0.00003832528,0.00001157447,0.00004311222,0.01282682,0.9624407,0.022783,0.00004952315,0.001626277],"study_design_scores_gemma":[0.0003207631,0.0000203398,0.000006730285,0.00005976214,0.00001386387,0.00002939379,0.0009909048,0.0004452366,0.9810874,0.00701801,0.009682287,0.0003252889],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.645178,0.004450744,0.346123,0.0001234304,0.001202919,0.000165892,0.0001877975,0.002097883,0.0004704433],"genre_scores_gemma":[0.9620734,0.001061949,0.03626708,0.00002960375,0.0001498569,0.000213081,0.00006670222,0.00008070858,0.00005757317],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3168955,"threshold_uncertainty_score":0.9999683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00673911449210508,"score_gpt":0.1937830397706286,"score_spread":0.1870439252785235,"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."}}