{"id":"W2430964300","doi":"10.1038/srep18978","title":"Improved Li storage performance in SnO2 nanocrystals by a synergetic doping","year":2016,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advancements in Battery Materials","field":"Engineering","cited_by":103,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Henan University; Division of Materials Sciences and Engineering; National Natural Science Foundation of China; UT-Battelle; National High-tech Research and Development Program; Innovation Scientists and Technicians Troop Construction Projects of Henan Province; Battelle; China Scholarship Council; U.S. Department of Energy","keywords":"Tin dioxide; Materials science; Doping; Cobalt; Nanocrystal; Electrochemistry; Lithium (medication); Chemical engineering; Tin; Electrode; Conductivity; Phase (matter); Nanotechnology; Microstructure; Ionic conductivity; Chemistry; Optoelectronics; Composite material; Metallurgy; Physical chemistry","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":[0.00008029639,0.0002946671,0.0002102985,0.0001507769,0.0001177784,0.0003348878,0.0002427556,0.0002680378,0.0004441902],"category_scores_gemma":[0.0001304502,0.0001244997,0.0001499111,0.0001500145,0.000130524,0.0003048716,0.0001791943,0.0001541341,0.0001997009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003240649,"about_ca_system_score_gemma":0.0001678545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001074463,"about_ca_topic_score_gemma":0.003321632,"domain_scores_codex":[0.9999056,0.000007472433,0.0000108804,0.00003009157,0.0000331307,0.00001289779],"domain_scores_gemma":[0.9999428,0.00000618703,0.00001129861,0.000004915632,0.00002487722,0.000009900168],"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":[0.0000560198,0.00001750646,0.0001592599,0.00002529903,0.000004384229,0.00003078224,0.000008431776,0.00007078899,0.9983574,0.0000983,0.00003558659,0.001136205],"study_design_scores_gemma":[0.00000897459,0.0000648459,0.0005486748,0.000001891632,0.00001032901,0.00005812671,0.000009421009,0.002146035,0.9962844,0.00001905259,0.0008440365,0.00000414786],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951286,0.0005344916,0.001952591,0.00004439599,0.00003040567,0.000009900466,0.00009076842,0.00004958998,0.002159295],"genre_scores_gemma":[0.9949555,0.0003163427,0.002803507,0.00001934472,0.000009197239,0.00001438148,0.0001482266,0.00002052388,0.00171288],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001074463,"threshold_uncertainty_score":0.002351284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006944241210920096,"score_gpt":0.210515603760568,"score_spread":0.2035713625496479,"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."}}