{"id":"W2003080230","doi":"10.1016/j.jpowsour.2013.09.069","title":"In situ Scanning electron microscope study and microstructural evolution of nano silicon anode for high energy Li-ion batteries","year":2013,"lang":"en","type":"article","venue":"Journal of Power Sources","topic":"Advancements in Battery Materials","field":"Engineering","cited_by":101,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hydro-Québec","funders":"U.S. Department of Energy; U.S. Department of Defense","keywords":"Scanning electron microscope; Anode; Materials science; Silicon; Sintering; Particle (ecology); Battery (electricity); Electrode; Ion; Chemical engineering; Nano-; Particle size; Electrochemistry; Composite material; Nanotechnology; Metallurgy; 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":[0.00008576021,0.0001549107,0.000143591,0.0002316387,0.000222126,0.0002281277,0.0002553461,0.0003065977,0.001289633],"category_scores_gemma":[0.0001222281,0.0002320335,0.0001427954,0.000165516,0.0001714752,0.0003211982,0.0001127652,0.0002323616,0.0001615255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002099031,"about_ca_system_score_gemma":0.0001362803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000798878,"about_ca_topic_score_gemma":0.001907094,"domain_scores_codex":[0.9999555,0.000002432649,0.000003101919,0.00000934672,0.00002276372,0.000006819802],"domain_scores_gemma":[0.9999112,0.00001806104,0.00001532735,0.000009838555,0.00003875599,0.000006751044],"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":[0.00004898844,0.00001570609,0.0005508425,0.00003820208,0.000003946001,0.00009321167,0.00005829856,0.0001731679,0.9976113,0.0001111556,0.00007350298,0.001221726],"study_design_scores_gemma":[0.000009237428,0.0001401483,0.01589317,0.000007146686,0.00001853847,0.0003468491,0.0001923293,0.005159599,0.9760993,0.00009592575,0.002029895,0.000007986219],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960496,0.0003610772,0.001325835,0.00006450972,0.00001753179,0.000005939999,0.000155788,0.00003274857,0.001986971],"genre_scores_gemma":[0.9960951,0.0002328983,0.001578419,0.00001678951,0.000008287095,0.000005711836,0.0001248031,0.00001085168,0.001927044],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001289633,"threshold_uncertainty_score":0.004314244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004368458243274339,"score_gpt":0.2235548151080437,"score_spread":0.2191863568647693,"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."}}