{"id":"W2962944457","doi":"10.1039/c9se00341j","title":"Graphene quantum dot induced tunable growth of nanostructured MnCo<sub>2</sub>O<sub>4.5</sub> composites for high-performance supercapacitors","year":2019,"lang":"en","type":"article","venue":"Sustainable Energy & Fuels","topic":"Supercapacitor Materials and Fabrication","field":"Materials Science","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"Regional Municipality of Waterloo; National Institute for Nanotechnology; University of Waterloo","funders":"Waterloo Institute for Nanotechnology, University of Waterloo; Natural Sciences and Engineering Research Council of Canada; University of Waterloo","keywords":"Supercapacitor; Quantum dot; Graphene; Materials science; Nanotechnology; Electrochemistry; Graphene quantum dot; Composite material; Morphology (biology); Electrode; Chemistry","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":[0.00004311491,0.0002169541,0.0001099091,0.0001612846,0.0001073622,0.0001664806,0.0001995047,0.000238872,0.0005835501],"category_scores_gemma":[0.0001025976,0.0001392433,0.0001145094,0.0001467967,0.0002024672,0.0001819881,0.0001836115,0.0002285073,0.0001059374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003230048,"about_ca_system_score_gemma":0.0001202581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009878894,"about_ca_topic_score_gemma":0.003249085,"domain_scores_codex":[0.9999404,0.000003701012,0.000003454473,0.00001718915,0.00002468654,0.00001063369],"domain_scores_gemma":[0.9999576,0.000005421547,0.00001421965,0.000005267603,0.000008916543,0.000008619658],"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":[0.000009573507,0.000005182904,0.00005986576,0.00001428345,0.000001384603,0.00002033332,0.0000103932,0.0001149521,0.9989096,0.00008679909,0.00003831909,0.0007292704],"study_design_scores_gemma":[0.000004207649,0.00001885959,0.0008430792,0.000001154525,0.000002228658,0.00002380145,0.000008421244,0.001622055,0.9968385,0.00002392861,0.0006098608,0.000003956179],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9911624,0.0003369023,0.005553147,0.00008995746,0.00004185166,0.00002376968,0.0001502144,0.0001931689,0.002448534],"genre_scores_gemma":[0.9943903,0.0001126276,0.004339771,0.00002104966,0.000003311468,0.00001276784,0.00005808374,0.00002197681,0.001040071],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009878894,"threshold_uncertainty_score":0.002343535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006931059531375279,"score_gpt":0.1962120100785755,"score_spread":0.1892809505472002,"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."}}