{"id":"W2309684671","doi":"10.1149/ma2016-03/2/180","title":"Hydrothermal Synthesis and Characterization of Co<sub>2</sub>GeO<sub>4</sub>/Rgo@C Ternary Composite As Negative Electrodes for Li-Ion Batteries","year":2016,"lang":"en","type":"article","venue":"ECS Meeting Abstracts","topic":"Advancements in Battery Materials","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Thermogravimetric analysis; Composite number; Ternary operation; Materials science; Graphene; High-resolution transmission electron microscopy; Electrolyte; Oxide; Chemical engineering; Calcination; Hydrothermal circulation; Nanotechnology; Electrode; Composite material; Chemistry; Transmission electron microscopy; Metallurgy; Catalysis; Physical chemistry; Organic 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":[0.00008152905,0.0002178001,0.0002947219,0.0002368813,0.0001536163,0.0002810728,0.0002082324,0.0003383829,0.000611213],"category_scores_gemma":[0.0001967354,0.0001220435,0.0001480518,0.00019306,0.0001852003,0.0002397001,0.0001505449,0.0002351064,0.0001927504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002812741,"about_ca_system_score_gemma":0.0002067437,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006729465,"about_ca_topic_score_gemma":0.002092241,"domain_scores_codex":[0.9999242,0.000005137053,0.000006584391,0.00001507162,0.0000367728,0.0000122864],"domain_scores_gemma":[0.9999069,0.00001216817,0.00002689196,0.000008142346,0.00003035517,0.00001542271],"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":[0.00002008544,0.000006755407,0.0001072881,0.00004375461,0.000001706792,0.00002722284,0.000006144461,0.00009413055,0.9989767,0.00002197293,0.0000150351,0.0006791819],"study_design_scores_gemma":[0.000002836415,0.0000533847,0.002297801,0.000002391701,0.0000113075,0.00009008741,0.00001580701,0.00101773,0.9956101,0.00001951174,0.0008728213,0.000006275787],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902723,0.001189435,0.006445956,0.00008066733,0.00003939248,0.00004774238,0.000289418,0.00009794802,0.001537159],"genre_scores_gemma":[0.990984,0.00038787,0.006789249,0.00002940908,0.000007270392,0.00002627975,0.000218479,0.000026279,0.001531157],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006729465,"threshold_uncertainty_score":0.002044737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00813192721498672,"score_gpt":0.2182491914495947,"score_spread":0.210117264234608,"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."}}